CVPR 2018 追踪之论文纲要（修正于2020.08.28）
- 讲在前面
- 论文目录
讲在前面
- 论坛很多博客都对论文做了总结和分类，但就医学领域而言，对这些论文的筛选信息显然需要更加精细的把控，所以自己对这979篇的论文做一个大致从名称上的筛选，希望能找到些能解决当前问题的答案。
- 论文链接建议直接Google论文名，比去各种论文或顶会网站找不知道快捷多少。
- 下面皆为机器翻译以方便我第一次筛选，我会慢慢修正，但现在请结合。有兴趣的可以问我要处理这些论文并自动翻译的脚本。
- Respect！
论文目录
| 论文 | 概要 |
|---|---|
| 1.2D_3D Pose Estimation and Action Recognition Using Multitask Deep Learning 使用多任务深度学习的2D_3D姿势估计和动作识别 | |
| 2.3D Human Pose Estimation in the Wild by Adversarial Learning 通过对抗性学习在野外进行3D人体姿势估计 | |
| 3.3D Human Sensing, Action and Emotion Recognition in Robot Assisted Therapy of Children With Autism 孤独症儿童机器人辅助治疗中的3D人体感应，动作和情感识别 | |
| 4.3D Object Detection With Latent Support Surfaces 具有潜在支撑面的3D对象检测 | |
| 5.3D Pose Estimation and 3D Model Retrieval for Objects in the Wild 野外物体的3D姿势估计和3D模型检索 | |
| 6.3D-RCNN: Instance-Level 3D Object Reconstruction via Render-and-Compare 3D-RCNN：通过渲染和比较重建实例级3D对象 | |
| 7.3D Registration of Curves and Surfaces Using Local Differential Information 使用局部微分信息进行曲线和曲面的3D配准 | |
| 8.3D Semantic Segmentation With Submanifold Sparse Convolutional Networks 子流形稀疏卷积网络的3D语义分割 | |
| 9.3D Semantic Trajectory Reconstruction From 3D Pixel Continuum 从3D像素连续体重建3D语义轨迹 | |
| 10.4DFAB: A Large Scale 4D Database for Facial Expression Analysis and Biometric Applications 4DFAB：用于面部表情分析和生物识别应用程序的大规模4D数据库 | |
| 11.4D Human Body Correspondences From Panoramic Depth Maps 全景深度图的4D人体对应 | |
| 12.A2-RL: Aesthetics Aware Reinforcement Learning for Image Cropping A2-RL：用于图像裁剪的美学意识增强学习 | |
| 13.A Bi-Directional Message Passing Model for Salient Object Detection 显着目标检测的双向消息传递模型 | |
| 14.A Biresolution Spectral Framework for Product Quantization 用于产品量化的双分辨率光谱框架 | |
| 15.A Causal And-Or Graph Model for Visibility Fluent Reasoning in Tracking Interacting Objects 交互对象跟踪中可视性推理的因果图模型 | |
| 16.Accurate and Diverse Sampling of Sequences Based on a “Best of Many” Sample Objective 基于“多个最佳”样本目标的序列的准确多样采样 | |
| 17.A Certifiably Globally Optimal Solution to the Non-Minimal Relative Pose Problem 非最小相对姿势问题的可证明的全局最优解 | |
| 18.A Closer Look at Spatiotemporal Convolutions for Action Recognition 近距离观察时空卷积的动作识别 | |
| 19.A Common Framework for Interactive Texture Transfer 交互式纹理传输的通用框架 | |
| 20.A Constrained Deep Neural Network for Ordinal Regression 序数回归的约束深度神经网络 | |
| 21.Action Sets: Weakly Supervised Action Segmentation Without Ordering Constraints 动作集：没有顺序约束的弱监督动作细分 | |
| 22.Active Fixation Control to Predict Saccade Sequences 主动注视控制可预测扫视序列 | |
| 23.Actor and Action Video Segmentation From a Sentence 句子中的演员和动作视频分割 | |
| 24.Actor and Observer: Joint Modeling of First and Third-Person Videos 演员和观察员：第一人称和第三人称视频的联合建模 | |
| 25.AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation AdaDepth：用于深度估计的无监督内容一致适应 | |
| 26.A Deeper Look at Power Normalizations 深入了解功率归一化 | |
| 27.Adversarial Complementary Learning for Weakly Supervised Object Localization 弱监督对象定位的对抗互补学习 | |
| 28.Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data 对抗性数据编程：使用GAN缓解标签化数据的瓶颈 | |
| 29.Adversarial Feature Augmentation for Unsupervised Domain Adaptation 无监督域自适应的对抗特征增强 | |
| 30.Adversarially Learned One-Class Classifier for Novelty Detection 对抗性学习的一类分类器，用于新颖性检测 | |
| 31.Adversarially Occluded Samples for Person Re-Identification 对抗性样本用于人员重新识别 | |
| 32.A Face-to-Face Neural Conversation Model 面对面的神经对话模型 | |
| 33.A Fast Resection-Intersection Method for the Known Rotation Problem 已知旋转问题的快速后方交集方法 | |
| 34.A Generative Adversarial Approach for Zero-Shot Learning From Noisy Texts 一种从嘈杂文本中零接触学习的生成对抗方法 | |
| 35.A Hierarchical Generative Model for Eye Image Synthesis and Eye Gaze Estimation 眼睛图像合成和眼睛注视估计的分层生成模型 | |
| 36.A High-Quality Denoising Dataset for Smartphone Cameras 用于智能手机相机的高质量降噪数据集 | |
| 37.A Hybrid l1-l0 Layer Decomposition Model for Tone Mapping 用于色调映射的混合l1-l0层分解模型 | |
| 38.Aligning Infinite-Dimensional Covariance Matrices in Reproducing Kernel Hilbert Spaces for Domain Adaptation 对齐域希尔伯特希尔伯特空间中的无限维协方差矩阵的对齐 | |
| 39.Alive Caricature From 2D to 3D 从2D到3D的生动漫画 | |
| 40.A Low Power, High Throughput, Fully Event-Based Stereo System 低功耗，高吞吐量，完全基于事件的立体声系统 | |
| 41.Alternating-Stereo VINS: Observability Analysis and Performance Evaluation 交替立体VINS：可观察性分析和性能评估 | |
| 42.A Memory Network Approach for Story-Based Temporal Summarization of 360deg Videos 基于故事的360deg视频时间摘要的记忆网络方法 | |
| 43.A Minimalist Approach to Type-Agnostic Detection of Quadrics in Point Clouds 点云中二次元的类型不可知检测的极简方法 | |
| 44.AMNet: Memorability Estimation With Attention AMNet：具有记忆力的评估 | |
| 45.Analysis of Hand Segmentation in the Wild 野外手部分割分析 | |
| 46.Analytical Modeling of Vanishing Points and Curves in Catadioptric Cameras 折反射相机中消失点和曲线的解析模型 | |
| 47.Analytic Expressions for Probabilistic Moments of PL-DNN With Gaussian Input 高斯输入的PL-DNN概率矩的解析表达式 | |
| 48.Analyzing Filters Toward Efficient ConvNet 分析面向高效ConvNet的过滤器 | |
| 49.An Analysis of Scale Invariance in Object Detection SNIP 目标检测SNIP中尺度不变性的分析 | |
| 50.Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation 卷积网络中无监督生物医学分割的解剖先验 |
| 论文 | 概要 |
|---|---|
| 51.An Efficient and Provable Approach for Mixture Proportion Estimation Using Linear Independence Assumption 使用线性独立假设的混合比例估计的一种有效且可行的方法 | |
| 52.An End-to-End TextSpotter With Explicit Alignment and Attention 具有明确对齐和注意力的端到端TextSpotter | |
| 53.A Network Architecture for Point Cloud Classification via Automatic Depth Images Generation 通过自动深度图像生成进行点云分类的网络架构 | |
| 54.A Neural Multi-Sequence Alignment TeCHnique (NeuMATCH) 神经多序列比对技术（NeuMATCH） | |
| 55.Anticipating Traffic Accidents With Adaptive Loss and Large-Scale Incident DB 利用自适应丢失和大规模事件数据库预测交通事故 | |
| 56.An Unsupervised Learning Model for Deformable Medical Image Registration 可变形医学图像配准的无监督学习模型 | |
| 57.AON: Towards Arbitrarily-Oriented Text Recognition AON：面向任意方向的文本识别 | |
| 58.A Papier-Mache Approach to Learning 3D Surface Generation 学习3D曲面生成的Papier-Mache方法 | |
| 59.A Perceptual Measure for Deep Single Image Camera Calibration 深度单像相机校准的感官测量 | |
| 60.Aperture Supervision for Monocular Depth Estimation 用于单眼深度估计的光圈监控 | |
| 61.A PID Controller Approach for Stochastic Optimization of Deep Networks 用于深度网络随机优化的PID控制器方法 | |
| 62.A Pose-Sensitive Embedding for Person Re-Identification With Expanded Cross Neighborhood Re-Ranking 具有扩展的跨邻域重新排列的姿势重新识别的姿势识别嵌入 | |
| 63.Appearance-and-Relation Networks for Video Classification 视频分类的外观和关系网络 | |
| 64.A Prior-Less Method for Multi-Face Tracking in Unconstrained Videos 无约束视频中多面跟踪的一种先验减少方法 | |
| 65.Arbitrary Style Transfer With Deep Feature Reshuffle 任意样式转移，具有深层功能重组 | |
| 66.A Revised Underwater Image Formation Model 修订后的水下成像模型 | |
| 67.Are You Talking to Me? Reasoned Visual Dialog Generation Through Adversarial Learning 你在跟我讲话吗？通过对抗学习进行合理的视觉对话生成 | |
| 68.A Robust Method for Strong Rolling Shutter Effects Correction Using Lines With Automatic Feature Selection 一种具有自动特征选择线的强力滚动快门效果校正的鲁棒方法 | |
| 69.Art of Singular Vectors and Universal Adversarial Perturbations 奇异向量和普遍对抗性摄动的艺术 | |
| 70.Attend and Interact: Higher-Order Object Interactions for Video Understanding 参加和交互：用于视频理解的高阶对象交互 | |
| 71.Attentional ShapeContextNet for Point Cloud Recognition 注意ShapeContextNet用于点云识别 | |
| 72.Attention-Aware Compositional Network for Person Re-Identification 用于人员重新识别的注意感知组成网络 | |
| 73.Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification 注意力集群：基于纯粹注意力的视频分类局部特征集成 | |
| 74.Attentive Fashion Grammar Network for Fashion Landmark Detection and Clothing Category Classification 专注于时尚地标检测和服装类别分类的时尚语法网络 | |
| 75.Attentive Generative Adversarial Network for Raindrop Removal From a Single Image 细心的生成对抗网络，用于从单个图像中去除雨滴 | |
| 76.AttnGAN: Fine-Grained Text to Image Generation With Attentional Generative Adversarial Networks AttnGAN：细化文本到带有注意生成对抗网络的图像生成 | |
| 77.A Twofold Siamese Network for Real-Time Object Tracking 用于实时对象跟踪的双重连体网络 | |
| 78.A Two-Step Disentanglement Method 两步解缠法 | |
| 79.Audio to Body Dynamics 音频到人体动力学 | |
| 80.Augmented Skeleton Space Transfer for Depth-Based Hand Pose Estimation 基于深度的手部姿势估计的增强骨架空间传递 | |
| 81.Augmenting Crowd-Sourced 3D Reconstructions Using Semantic Detections 使用语义检测增强人群源3D重建 | |
| 82.A Unifying Contrast Maximization Framework for Event Cameras, With Applications to Motion, Depth, and Optical Flow Estimation 用于事件摄像机的统一对比度最大化框架，应用于运动，深度和光流估计 | |
| 83.Automatic 3D Indoor Scene Modeling From Single Panorama 从单个全景图进行自动3D室内场景建模 | |
| 84.AVA: A Video Dataset of Spatio-Temporally Localized Atomic Visual Actions AVA：时空局部原子视觉动作的视频数据集 | |
| 85.A Variational U-Net for Conditional Appearance and Shape Generation 用于条件外观和形状生成的变体U-网 | |
| 86.Avatar-Net: Multi-Scale Zero-Shot Style Transfer by Feature Decoration Avatar-Net：通过特征装饰进行多尺度零射击样式转移 | |
| 87.A Weighted Sparse Sampling and Smoothing Frame Transition Approach for Semantic Fast-Forward First-Person Videos 语义快进第一人称视频的加权稀疏采样和平滑帧过渡方法 | |
| 88.Baseline Desensitizing in Translation Averaging 平均翻译中的基线脱敏 | |
| 89.Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions 在不断变化的条件下对6DOF户外视觉本地化进行基准测试 | |
| 90.Between-Class Learning for Image Classification 课间学习进行图像分类 | |
| 91.Beyond Grobner Bases: Basis Selection for Minimal Solvers Grobner基础之外：最小求解器的基础选择 | |
| 92.Beyond Holistic Object Recognition: Enriching Image Understanding With Part States 超越整体物体识别：利用零件状态丰富图像理解 | |
| 93.Beyond the Pixel-Wise Loss for Topology-Aware Delineation 超越像素明智的拓扑描述 | |
| 94.Beyond Trade-Off: Accelerate FCN-Based Face Detector With Higher Accuracy 权衡之外：高精度加速基于FCN的人脸检测器 | |
| 95.Bidirectional Attentive Fusion With Context Gating for Dense Video Captioning 具有上下文门控功能的双向注意力融合，用于密集视频字幕 | |
| 96.Bidirectional Retrieval Made Simple 双向检索变得简单 | |
| 97.Bilateral Ordinal Relevance Multi-Instance Regression for Facial Action Unit Intensity Estimation 双边序贯相关性多实例回归用于面部动作单位强度估计 | |
| 98.Blazingly Fast Video Object Segmentation With Pixel-Wise Metric Learning 像素明智的度量学习，实现了惊人的快速视频对象分割 | |
| 99.Blind Predicting Similar Quality Map for Image Quality Assessment 盲预测相似质量图进行图像质量评估 | |
| 100.BlockDrop: Dynamic Inference Paths in Residual Networks BlockDrop：残差网络中的动态推理路径 |
| 论文 | 概要 |
|---|---|
| 101.Boosting Adversarial Attacks With Momentum 用动量来增强对抗性攻击 | |
| 102.Boosting Domain Adaptation by Discovering Latent Domains 通过发现潜在域来促进域适应 | |
| 103.Boosting Self-Supervised Learning via Knowledge Transfer 通过知识转移促进自我监督学习 | |
| 104.Bootstrapping the Performance of Webly Supervised Semantic Segmentation 引导Webly监督的语义分割的性能 | |
| 105.Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering 自下而上和自上而下的注意力，用于图像字幕和视觉问题解答 | |
| 106.Boundary Flow: A Siamese Network That Predicts Boundary Motion Without Training on Motion 边界流：无需运动训练就可以预测边界运动的暹罗网络 | |
| 107.BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning BPGrad：通过分支和修剪在深度学习中实现全球最优 | |
| 108.Burst Denoising With Kernel Prediction Networks 内核预测网络进行突发去噪 | |
| 109.Camera Pose Estimation With Unknown Principal Point 主点未知的相机姿态估计 | |
| 110.Camera Style Adaptation for Person Re-Identification 用于重新识别人的相机样式适应 | |
| 111.Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet? 时空3D CNN是否可以追溯2D CNN和ImageNet的历史？ | |
| 112.CarFusion: Combining Point Tracking and Part Detection for Dynamic 3D Reconstruction of Vehicles CarFusion：结合点跟踪和零件检测用于车辆的动态3D重构 | |
| 113.CartoonGAN: Generative Adversarial Networks for Photo Cartoonization CartoonGAN：用于照片卡通化的生成对抗网络 | |
| 114.Cascaded Pyramid Network for Multi-Person Pose Estimation 用于多人姿势估计的级联金字塔网络 | |
| 115.Cascade R-CNN: Delving Into High Quality Object Detection 级联R-CNN：深入研究高质量目标检测 | |
| 116.Categorizing Concepts With Basic Level for Vision-to-Language 将基本概念归类为视觉到语言 | |
| 117.CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation CBMV：用于视差估计的合并双向匹配量 | |
| 118.Classification-Driven Dynamic Image Enhancement 分类驱动的动态图像增强 | |
| 119.Classifier Learning With Prior Probabilities for Facial Action Unit Recognition 具有面部动作单元识别先验概率的分类器学习 | |
| 120.ClcNet: Improving the Efficiency of Convolutional Neural Network Using Channel Local Convolutions ClcNet：使用通道局部卷积提高卷积神经网络的效率 | |
| 121.CleanNet: Transfer Learning for Scalable Image Classifier Training With Label Noise CleanNet：带标签噪声的可扩展图像分类器培训的转移学习 | |
| 122.CLEAR: Cumulative LEARning for One-Shot One-Class Image Recognition 清除：一键式一类图像识别的累积学习 | |
| 123.Clinical Skin Lesion Diagnosis Using Representations Inspired by Dermatologist Criteria 使用皮肤科医生标准启发的表征进行临床皮肤病变诊断 | |
| 124.CLIP-Q: Deep Network Compression Learning by In-Parallel Pruning-Quantization CLIP-Q：通过并行修剪量化进行深度网络压缩学习 | |
| 125.ClusterNet: Detecting Small Objects in Large Scenes by Exploiting Spatio-Temporal Information ClusterNet：通过利用时空信息检测大型场景中的小物体 | |
| 126.CNN Based Learning Using Reflection and Retinex Models for Intrinsic Image Decomposition 基于CNN的使用反射和Retinex模型进行内在图像分解的学习 | |
| 127.CNN Driven Sparse Multi-Level B-Spline Image Registration CNN驱动的稀疏多级B样条图像配准 | |
| 128.CNN in MRF: Video Object Segmentation via Inference in a CNN-Based Higher-Order Spatio-Temporal MRF MRF中的CNN：在基于CNN的高阶时空MRF中通过推理进行视频对象分割 | |
| 129.COCO-Stuff: Thing and Stuff Classes in Context COCO-Stuff：上下文中的事物和事物类 | |
| 130.CodeSLAM – Learning a Compact, Optimisable Representation for Dense Visual SLAM CodeSLAM-学习密集Visual SLAM的紧凑，可优化表示形式 | |
| 131.Coding Kendall’s Shape Trajectories for 3D Action Recognition 编码Kendall的形状轨迹以进行3D动作识别 | |
| 132.Collaborative and Adversarial Network for Unsupervised Domain Adaptation 无监督域自适应的协作和对抗网络 | |
| 133.Compare and Contrast: Learning Prominent Visual Differences 比较和对比：学习明显的视觉差异 | |
| 134.Compassionately Conservative Balanced Cuts for Image Segmentation 慷慨保守的平衡切割用于图像分割 | |
| 135.Compressed Video Action Recognition 压缩视频动作识别 | |
| 136.CondenseNet: An Efficient DenseNet Using Learned Group Convolutions CondenseNet：使用学习的组卷积的高效DenseNet | |
| 137.Conditional Generative Adversarial Network for Structured Domain Adaptation 结构化领域适应的条件生成对抗网络 | |
| 138.Conditional Image-to-Image Translation 有条件的图像到图像翻译 | |
| 139.Conditional Probability Models for Deep Image Compression 深度图像压缩的条件概率模型 | |
| 140.Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images 将像素连接到隐私和实用程序：自动删除图像中的私人信息 | |
| 141.Consensus Maximization for Semantic Region Correspondences 语义区域对应的共识最大化 | |
| 142.Content-Sensitive Supervoxels via Uniform Tessellations on Video Manifolds 通过视频流形上的统一镶嵌来对内容敏感的超级体素 | |
| 143.Context-Aware Deep Feature Compression for High-Speed Visual Tracking 用于高速视觉跟踪的上下文感知深度特征压缩 | |
| 144.Context-Aware Synthesis for Video Frame Interpolation 视频帧插值的上下文感知综合 | |
| 145.Context Contrasted Feature and Gated Multi-Scale Aggregation for Scene Segmentation 用于场景分割的上下文对比特征和门控多尺度聚合 | |
| 146.Context Embedding Networks 上下文嵌入网络 | |
| 147.Context Encoding for Semantic Segmentation 用于语义分割的上下文编码 | |
| 148.Continuous Relaxation of MAP Inference: A Nonconvex Perspective MAP推理的连续松弛：非凸视角 | |
| 149.Controllable Video Generation With Sparse Trajectories 具有稀疏轨迹的可控视频生成 | |
| 150.Convolutional Image Captioning 卷积图像字幕 |
| 论文 | 概要 |
|---|---|
| 151.Convolutional Neural Networks With Alternately Updated Clique 具有交替更新的派系的卷积神经网络 | |
| 152.Convolutional Sequence to Sequence Model for Human Dynamics 卷积序列到人类动力学序列模型 | |
| 153.Correlation Tracking via Joint Discrimination and Reliability Learning 通过联合鉴别和可靠性学习进行关联跟踪 | |
| 154.CosFace: Large Margin Cosine Loss for Deep Face Recognition CosFace：用于识别深脸的大余弦余弦损失 | |
| 155.Coupled End-to-End Transfer Learning With Generalized Fisher Information 端到端迁移学习与广义Fisher信息相结合 | |
| 156.Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning 通过深度强化学习制作用于图像还原的工具链 | |
| 157.Creating Capsule Wardrobes From Fashion Images 从时尚形象创建胶囊衣柜 | |
| 158.Cross-Dataset Adaptation for Visual Question Answering 跨数据集自适应以解决视觉问题 | |
| 159.Cross-Domain Self-Supervised Multi-Task Feature Learning Using Synthetic Imagery 使用合成影像的跨域自我监督多任务特征学习 | |
| 160.Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation 通过渐进域自适应进行跨域弱监督对象检测 | |
| 161.Cross-Modal Deep Variational Hand Pose Estimation 跨模态深度变化手姿势估计 | |
| 162.Cross-View Image Synthesis Using Conditional GANs 使用条件GAN的跨视图图像合成 | |
| 163.Crowd Counting via Adversarial Cross-Scale Consistency Pursuit 通过对抗性跨尺度一致性追求进行人群计数 | |
| 164.Crowd Counting With Deep Negative Correlation Learning 深度负相关学习的人群计数 | |
| 165.CRRN: Multi-Scale Guided Concurrent Reflection Removal Network CRRN：多尺度引导并发反射去除网络 | |
| 166.CSGNet: Neural Shape Parser for Constructive Solid Geometry CSGNet：用于构造实体几何的神经形状解析器 | |
| 167.CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes CSRNet：扩展卷积神经网络，用于了解高度拥挤的场景 | |
| 168.Cube Padding for Weakly-Supervised Saliency Prediction in 360deg Videos 360度视频中弱监督显着性预测的多维数据集填充 | |
| 169.Curve Reconstruction via the Global Statistics of Natural Curves 通过自然曲线的整体统计量重建曲线 | |
| 170.Customized Image Narrative Generation via Interactive Visual Question Generation and Answering 通过交互式视觉问题生成和回答定制的图像叙事生成 | |
| 171.CVM-Net: Cross-View Matching Network for Image-Based Ground-to-Aerial Geo-Localization CVM-Net：用于基于图像的地对空地理定位的跨视图匹配网络 | |
| 172.DA-GAN: Instance-Level Image Translation by Deep Attention Generative Adversarial Networks DA-GAN：深度注意生成对抗网络的实例级图像翻译 | |
| 173.Data Distillation: Towards Omni-Supervised Learning 数据提炼：走向全监督学习 | |
| 174.DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks DeblurGAN：使用条件对抗网络进行盲运动去模糊 | |
| 175.DecideNet: Counting Varying Density Crowds Through Attention Guided Detection and Density Estimation DecideNet：通过注意力指导的检测和密度估计计算不同的密度人群 | |
| 176.Decorrelated Batch Normalization 装饰相关的批次标准化 | |
| 177.Decoupled Networks 解耦网络 | |
| 178.Deep Adversarial Metric Learning 深度对抗度量学习 | |
| 179.Deep Adversarial Subspace Clustering 深度对抗子空间聚类 | |
| 180.Deep Back-Projection Networks for Super-Resolution 深度背投网络可实现超高分辨率 | |
| 181.Deep Cauchy Hashing for Hamming Space Retrieval 深层柯西散列用于汉明空间检索 | |
| 182.Deep Cocktail Network: Multi-Source Unsupervised Domain Adaptation With Category Shift 深度鸡尾酒网络：具有类别转移的多源无监督域自适应 | |
| 183.Deep Cost-Sensitive and Order-Preserving Feature Learning for Cross-Population Age Estimation 用于跨人口年龄估计的深度成本敏感和顺序保留特征学习 | |
| 184.Deep Cross-Media Knowledge Transfer 深度跨媒体知识转移 | |
| 185.Deep Density Clustering of Unconstrained Faces 无约束面孔的深度密度聚类 | |
| 186.Deep Depth Completion of a Single RGB-D Image 单个RGB-D图像的深度完成 | |
| 187.Deep Diffeomorphic Transformer Networks 深微形变压器网络 | |
| 188.Deep End-to-End Time-of-Flight Imaging 深度端到端飞行时间成像 | |
| 189.Deep Extreme Cut: From Extreme Points to Object Segmentation 深度极限切割：从极限点到对象分割 | |
| 190.Deep Face Detector Adaptation Without Negative Transfer or Catastrophic Forgetting 无需负迁移或灾难性遗忘的深脸检测器自适应 | |
| 191.Deep Group-Shuffling Random Walk for Person Re-Identification 用于人员重新识别的深度群混洗随机游走 | |
| 192.Deep Hashing via Discrepancy Minimization 通过差异最小化进行深度哈希 | |
| 193.Deep Image Prior 深度图像先验 | |
| 194.Deep Layer Aggregation 深层聚合 | |
| 195.Deep Learning of Graph Matching 图匹配的深度学习 | |
| 196.Deep Learning Under Privileged Information Using Heteroscedastic Dropout 使用异方差辍学在特权信息下进行深度学习 | |
| 197.Deep Lesion Graphs in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-Scale Lesion Database 在野外的深部病变图：关系学习和在大量大型病变数据库中的重要放射图像发现的组织 | |
| 198.Deeply Learned Filter Response Functions for Hyperspectral Reconstruction 深度学习的滤波器响应函数，用于高光谱重建 | |
| 199.Deep Marching Cubes: Learning Explicit Surface Representations 深入进行中的立方体：学习明确的表面表示 | |
| 200.Deep Material-Aware Cross-Spectral Stereo Matching 深度材料感知跨谱立体匹配 |
| 论文 | 概要 |
|---|---|
| 201.Deep Mutual Learning 深度相互学习 | |
| 202.DeepMVS: Learning Multi-View Stereopsis DeepMVS：学习多视图立体视觉 | |
| 203.Deep Ordinal Regression Network for Monocular Depth Estimation 用于单眼深度估计的深度序数回归网络 | |
| 204.Deep Parametric Continuous Convolutional Neural Networks 深参量连续卷积神经网络 | |
| 205.Deep Photo Enhancer: Unpaired Learning for Image Enhancement From Photographs With GANs 深度照片增强器：使用GAN从照片中进行成对学习的图像增强 | |
| 206.Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition 基于骨骼的动作识别的深度渐进强化学习 | |
| 207.Deep Regression Forests for Age Estimation 深回归森林的年龄估算 | |
| 208.Deep Reinforcement Learning of Region Proposal Networks for Object Detection 用于对象检测的区域提议网络的深度强化学习 | |
| 209.Deep Semantic Face Deblurring 深层语义去模糊 | |
| 210.Deep Sparse Coding for Invariant Multimodal Halle Berry Neurons 不变多模态哈莉·贝瑞神经元的深度稀疏编码 | |
| 211.Deep Spatial Feature Reconstruction for Partial Person Re-Identification: Alignment-Free Approach 用于部分人员重新识别的深度空间特征重建：无路线方法 | |
| 212.Deep Spatio-Temporal Random Fields for Efficient Video Segmentation 深度时空随机场，用于有效的视频分割 | |
| 213.Deep Texture Manifold for Ground Terrain Recognition 用于地面地形识别的深纹理流形 | |
| 214.Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective 深度无监督的显着性检测：多重噪声标记 | |
| 215.Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation 深度视频超分辨率网络，使用动态上采样滤波器，无需显式运动补偿 | |
| 216.DeepVoting: A Robust and Explainable Deep Network for Semantic Part Detection Under Partial Occlusion DeepVoting：在部分遮挡下用于语义部分检测的强大且可解释的深度网络 | |
| 217.Defense Against Adversarial Attacks Using High-Level Representation Guided Denoiser 使用高级表示制导的降噪器防御对抗攻击 | |
| 218.Defense Against Universal Adversarial Perturbations 防御普遍的对抗性干扰 | |
| 219.Deflecting Adversarial Attacks With Pixel Deflection 通过像素偏转来对抗对手的攻击 | |
| 220.Defocus Blur Detection via Multi-Stream Bottom-Top-Bottom Fully Convolutional Network 通过多流底部-顶部-底部完全卷积网络进行散焦模糊检测 | |
| 221.Deformable GANs for Pose-Based Human Image Generation 用于基于姿势的人体图像生成的可变形GAN | |
| 222.Deformable Shape Completion With Graph Convolutional Autoencoders 图卷积自动编码器的可变形形状完成 | |
| 223.Deformation Aware Image Compression 变形感知图像压缩 | |
| 224.DeLS-3D: Deep Localization and Segmentation With a 3D Semantic Map DeLS-3D：具有3D语义图的深度定位和细分 | |
| 225.Demo2Vec: Reasoning Object Affordances From Online Videos Demo2Vec：从在线视频中推理出对象客流 | |
| 226.Dense 3D Regression for Hand Pose Estimation 手势姿势估计的密集3D回归 | |
| 227.DenseASPP for Semantic Segmentation in Street Scenes DenseASPP用于街道场景中的语义分割 | |
| 228.Dense Decoder Shortcut Connections for Single-Pass Semantic Segmentation 用于单遍语义分割的密集解码器快捷方式连接 | |
| 229.Densely Connected Pyramid Dehazing Network 密集连接的金字塔除雾网络 | |
| 230.DensePose: Dense Human Pose Estimation in the Wild DensePose：野外的密集人体姿势估计 | |
| 231.Density Adaptive Point Set Registration 密度自适应点集配准 | |
| 232.Density-Aware Single Image De-Raining Using a Multi-Stream Dense Network 使用多流密集网络的密度感知单图像降噪 | |
| 233.Depth and Transient Imaging With Compressive SPAD Array Cameras 压缩SPAD阵列摄像机的深度和瞬态成像 | |
| 234.Depth-Aware Stereo Video Retargeting 深度感知立体声视频重定向 | |
| 235.Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals 基于深度的3D手势估计：从当前成就到未来目标 | |
| 236.Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation 分离和适应：学习跨域解缠结的深度表示 | |
| 237.Detail-Preserving Pooling in Deep Networks 深度网络中保留细节的池 | |
| 238.Detect-and-Track: Efficient Pose Estimation in Videos 检测并跟踪：视频中的有效姿势估计 | |
| 239.Detect Globally, Refine Locally: A Novel Approach to Saliency Detection 全局检测，局部优化：显着性检测的新方法 | |
| 240.Detecting and Recognizing Human-Object Interactions 检测和识别人与物体的相互作用 | |
| 241.Differential Attention for Visual Question Answering 视觉问答中的注意差异 | |
| 242.Dimensionality’s Blessing: Clustering Images by Underlying Distribution 维数的祝福：通过基础分布将图像聚类 | |
| 243.Direction-Aware Spatial Context Features for Shadow Detection 用于阴影检测的方向感知空间上下文功能 | |
| 244.Direct Shape Regression Networks for End-to-End Face Alignment 直接形状回归网络用于端对端的面对齐 | |
| 245.Discovering Point Lights With Intensity Distance Fields 发现具有强度距离场的点光源 | |
| 246.Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs 离散连续ADMM用于高阶MRF中的转导推理 | |
| 247.Discriminability Objective for Training Descriptive Captions 训练描述性字幕的可分辨性目标 | |
| 248.Discriminative Learning of Latent Features for Zero-Shot Recognition 零射击识别的潜在特征的判别学习 | |
| 249.Disentangled Person Image Generation 纠缠人图像生成 | |
| 250.Disentangling 3D Pose in a Dendritic CNN for Unconstrained 2D Face Alignment 解开树枝状CNN中的3D姿势以实现不受约束的2D面部对齐 |
| 论文 | 概要 |
|---|---|
| 251.Disentangling Factors of Variation by Mixing Them 通过混合将变量分解开来 | |
| 252.Disentangling Features in 3D Face Shapes for Joint Face Reconstruction and Recognition 解开3D人脸形状的特征以进行联合人脸重建和识别 | |
| 253.Disentangling Structure and Aesthetics for Style-Aware Image Completion 解开结构和美学的风格感知图像完成 | |
| 254.Distort-and-Recover: Color Enhancement Using Deep Reinforcement Learning 失真与恢复：使用深度强化学习增强色彩 | |
| 255.Distributable Consistent Multi-Object Matching 可分配一致的多对象匹配 | |
| 256.DiverseNet: When One Right Answer Is Not Enough DiverseNet：当一个正确的答案还不够时 | |
| 257.Diversity Regularized Spatiotemporal Attention for Video-Based Person Re-Identification 基于视频的人员重新识别的多样性正则化时空注意 | |
| 258.Divide and Conquer for Full-Resolution Light Field Deblurring 分立制胜，实现全分辨率光场去模糊 | |
| 259.Divide and Grow: Capturing Huge Diversity in Crowd Images With Incrementally Growing CNN 分而成长：随着CNN的不断增长，捕捉人群图像中的巨大多样性 | |
| 260.Document Enhancement Using Visibility Detection 使用可见性检测增强文档 | |
| 261.DocUNet: Document Image Unwarping via a Stacked U-Net DocUNet：文档图像通过堆叠的U-Net变形 | |
| 262.Domain Adaptive Faster R-CNN for Object Detection in the Wild 用于野外目标检测的域自适应快速R-CNN | |
| 263.Domain Generalization With Adversarial Feature Learning 具有对抗性特征学习的领域概括 | |
| 264.Don’t Just Assume; Look and Answer: Overcoming Priors for Visual Question Answering 不要只是假设；外观和答案：克服视觉提问的先验 | |
| 265.DOTA: A Large-Scale Dataset for Object Detection in Aerial Images DOTA：用于航空图像中目标检测的大规模数据集 | |
| 266.DoubleFusion: Real-Time Capture of Human Performances With Inner Body Shapes From a Single Depth Sensor DoubleFusion：通过单个深度传感器实时捕获具有人体形状的人体表演 | |
| 267.DS*: Tighter Lifting-Free Convex Relaxations for Quadratic Matching Problems *DS ：针对二次匹配问题的更紧的免提凸松弛 | |
| 268.Dual Attention Matching Network for Context-Aware Feature Sequence Based Person Re-Identification 用于基于上下文感知特征序列的人员重新识别的双注意匹配网络 | |
| 269.Dual Skipping Networks 双跳网 | |
| 270.Duplex Generative Adversarial Network for Unsupervised Domain Adaptation 用于无监督域自适应的双工生成对抗网络 | |
| 271.DVQA: Understanding Data Visualizations via Question Answering DVQA：通过问答理解数据可视化 | |
| 272.Dynamic Feature Learning for Partial Face Recognition 动态特征学习用于部分人脸识别 | |
| 273.Dynamic Few-Shot Visual Learning Without Forgetting 无需忘记的动态少量视觉学习 | |
| 274.Dynamic Graph Generation Network: Generating Relational Knowledge From Diagrams 动态图生成网络：从图生成关系知识 | |
| 275.Dynamic Scene Deblurring Using Spatially Variant Recurrent Neural Networks 使用空间变异递归神经网络进行动态场景去模糊 | |
| 276.Dynamic-Structured Semantic Propagation Network 动态结构的语义传播网络 | |
| 277.Dynamic Video Segmentation Network 动态视频分割网络 | |
| 278.Dynamic Zoom-In Network for Fast Object Detection in Large Images 动态放大网络，可快速检测大图像中的物体 | |
| 279.Easy Identification From Better Constraints: Multi-Shot Person Re-Identification From Reference Constraints 从更好的约束中轻松识别：从参考约束中进行多次连发人员重新识别 | |
| 280.Edit Probability for Scene Text Recognition 编辑场景文本识别的概率 | |
| 281.Efficient and Deep Person Re-Identification Using Multi-Level Similarity 使用多级相似性进行有效的深度人员重新识别 | |
| 282.Efficient Diverse Ensemble for Discriminative Co-Tracking 高效的多元化集合体，可进行区分式协同跟踪 | |
| 283.Efficient Interactive Annotation of Segmentation Datasets With Polygon-RNN++ 使用Polygon-RNN ++的分段数据集的高效交互式注释 | |
| 284.Efficient Large-Scale Approximate Nearest Neighbor Search on OpenCL FPGA 在OpenCL FPGA上进行高效的大规模近似最近邻居搜索 | |
| 285.Efficient Optimization for Rank-Based Loss Functions 基于等级的损失函数的有效优化 | |
| 286.Efficient Parametrization of Multi-Domain Deep Neural Networks 多域深度神经网络的高效参数化 | |
| 287.Efficient, Sparse Representation of Manifold Distance Matrices for Classical Scaling 流形距离矩阵的有效，稀疏表示 | |
| 288.Efficient Subpixel Refinement With Symbolic Linear Predictors 使用符号线性预测器进行有效的亚像素细化 | |
| 289.Efficient Video Object Segmentation via Network Modulation 通过网络调制进行有效的视频对象分割 | |
| 290.Egocentric Activity Recognition on a Budget 预算中的自我中心活动识别 | |
| 291.Egocentric Basketball Motion Planning From a Single First-Person Image 从单个第一人称图像进行以自我为中心的篮球运动计划 | |
| 292.Eliminating Background-Bias for Robust Person Re-Identification 消除背景偏见，进行稳健的人员重新识别 | |
| 293.Embodied Question Answering 具体问题解答 | |
| 294.Emotional Attention: A Study of Image Sentiment and Visual Attention 情绪注意：图像情感和视觉注意的研究 | |
| 295.Empirical Study of the Topology and Geometry of Deep Networks 深度网络拓扑和几何的实证研究 | |
| 296.Encoding Crowd Interaction With Deep Neural Network for Pedestrian Trajectory Prediction 用深度神经网络编码人群交互作用以预测行人轨迹 | |
| 297.End-to-End Convolutional Semantic Embeddings 端到端卷积语义嵌入 | |
| 298.End-to-End Deep Kronecker-Product Matching for Person Re-Identification 端到端深度Kronecker产品匹配以重新识别人 | |
| 299.End-to-End Dense Video Captioning With Masked Transformer 带屏蔽变压器的端到端密集视频字幕 | |
| 300.End-to-End Flow Correlation Tracking With Spatial-Temporal Attention 时空注意的端到端流相关跟踪 |
| 论文 | 概要 |
|---|---|
| 301.End-to-End Learning of Keypoint Detector and Descriptor for Pose Invariant 3D Matching 姿势不变3D匹配的关键点检测器和描述符的端到端学习 | |
| 302.End-to-End Learning of Motion Representation for Video Understanding 端到端学习运动表示以了解视频 | |
| 303.End-to-End Recovery of Human Shape and Pose 人体形状和姿势的端到端恢复 | |
| 304.End-to-End Weakly-Supervised Semantic Alignment 端到端弱监督的语义对齐 | |
| 305.Enhancing the Spatial Resolution of Stereo Images Using a Parallax Prior 使用视差先验增强立体图像的空间分辨率 | |
| 306.Environment Upgrade Reinforcement Learning for Non-Differentiable Multi-Stage Pipelines 不可分多阶段管道的环境升级强化学习 | |
| 307.EPINET: A Fully-Convolutional Neural Network Using Epipolar Geometry for Depth From Light Field Images EPINET：一种全卷积神经网络，使用对极几何学从光场图像中提取深度 | |
| 308.Erase or Fill? Deep Joint Recurrent Rain Removal and Reconstruction in Videos 擦除还是填充？视频中的深层关节经常性除雨和重建 | |
| 309.Estimation of Camera Locations in Highly Corrupted Scenarios: All About That Base, No Shape Trouble 高度损坏的场景中摄像机位置的估计：关于该基准的所有信息，没有形状问题 | |
| 310.Event-Based Vision Meets Deep Learning on Steering Prediction for Self-Driving Cars 基于事件的愿景与无人驾驶汽车转向预测的深度学习相遇 | |
| 311.Every Smile Is Unique: Landmark-Guided Diverse Smile Generation 每个微笑都是独一无二的：具有地标性的多样化微笑产生 | |
| 312.Excitation Backprop for RNNs RNN的激励反向传播 | |
| 313.Explicit Loss-Error-Aware Quantization for Low-Bit Deep Neural Networks 低位深度神经网络的明确的丢失错误感知量化 | |
| 314.Exploiting Transitivity for Learning Person Re-Identification Models on a Budget 在预算中利用可传递性学习人的重新识别模型 | |
| 315.Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning 逐步利用未知：通过逐步学习对基于视频的一击式人员进行重新识别 | |
| 316.Exploring Disentangled Feature Representation Beyond Face Identification 探索超越人脸识别的非纠缠特征表示 | |
| 317.Extreme 3D Face Reconstruction: Seeing Through Occlusions 极端3D面部重建：透视遮挡 | |
| 318.Eye In-Painting With Exemplar Generative Adversarial Networks 使用示例性生成对抗网络进行眼睛内画 | |
| 319.Face Aging With Identity-Preserved Conditional Generative Adversarial Networks 保留身份的条件生成对抗网络的面孔老化 | |
| 320.FaceID-GAN: Learning a Symmetry Three-Player GAN for Identity-Preserving Face Synthesis FaceID-GAN：学习对称三层GAN来保持身份的人脸合成 | |
| 321.Facelet-Bank for Fast Portrait Manipulation Facelet-Bank用于快速人像操作 | |
| 322.Facial Expression Recognition by De-Expression Residue Learning 去表达残基学习的面部表情识别 | |
| 323.Factoring Shape, Pose, and Layout From the 2D Image of a 3D Scene 从3D场景的2D图像分解形状，姿势和布局 | |
| 324.Fast and Accurate Online Video Object Segmentation via Tracking Parts 通过跟踪部件快速，准确地在线分割视频对象 | |
| 325.Fast and Accurate Single Image Super-Resolution via Information Distillation Network 通过信息蒸馏网络实现快速，准确的单图像超分辨率 | |
| 326.Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting With a Single Convolutional Net 速度与激情：使用单个卷积网络进行实时端到端3D检测，跟踪和运动预测 | |
| 327.Fast and Robust Estimation for Unit-Norm Constrained Linear Fitting Problems 单位范数约束线性拟合问题的快速鲁棒估计 | |
| 328.Fast End-to-End Trainable Guided Filter 快速的端到端可训练导引滤波器 | |
| 329.Fast Monte-Carlo Localization on Aerial Vehicles Using Approximate Continuous Belief Representations 使用近似连续信念表示法对飞行器进行快速蒙特卡洛定位 | |
| 330.Fast Spectral Ranking for Similarity Search 相似搜索的快速光谱排名 | |
| 331.Fast Video Object Segmentation by Reference-Guided Mask Propagation 通过参考引导的遮罩传播进行快速视频对象分割 | |
| 332.FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis FeaStNet：用于3D形状分析的基于特征的图卷积 | |
| 333.Feature Generating Networks for Zero-Shot Learning 零发学习的特征生成网络 | |
| 334.Feature Mapping for Learning Fast and Accurate 3D Pose Inference From Synthetic Images 从合成图像中快速，准确地学习3D姿势推断的特征映射 | |
| 335.Feature Quantization for Defending Against Distortion of Images 防止图像失真的特征量化 | |
| 336.Feature Selective Networks for Object Detection 用于目标检测的特征选择网络 | |
| 337.Features for Multi-Target Multi-Camera Tracking and Re-Identification 多目标多摄像机跟踪和重新识别功能 | |
| 338.Feature Space Transfer for Data Augmentation 特征空间传输以增强数据 | |
| 339.Feature Super-Resolution: Make Machine See More Clearly 功能超高分辨率：使机器更加清晰 | |
| 340.Feedback-Prop: Convolutional Neural Network Inference Under Partial Evidence 反馈支持：部分证据下的卷积神经网络推理 | |
| 341.Few-Shot Image Recognition by Predicting Parameters From Activations 通过预测激活参数来进行少量图像识别 | |
| 342.FFNet: Video Fast-Forwarding via Reinforcement Learning FFNet：通过强化学习进行视频快速转发 | |
| 343.Fight Ill-Posedness With Ill-Posedness: Single-Shot Variational Depth Super-Resolution From Shading 与病态对抗病态：阴影的单发变化深度超级分辨率 | |
| 344.Finding Beans in Burgers: Deep Semantic-Visual Embedding With Localization 在汉堡中寻找豆子：具有本地化功能的深度语义视觉嵌入 | |
| 345.Finding “It”: Weakly-Supervised Reference-Aware Visual Grounding in Instructional Videos 找到“它”：教学视频中受弱监督的参考感知的视觉基础 | |
| 346.Finding Tiny Faces in the Wild With Generative Adversarial Network 利用生成对抗网络在野外寻找小脸 | |
| 347.Fine-Grained Video Captioning for Sports Narrative 体育叙事的细粒度视频字幕 | |
| 348.First-Person Hand Action Benchmark With RGB-D Videos and 3D Hand Pose Annotations 具有RGB-D视频和3D手势注释的第一人称手势基准 | |
| 349.Five-Point Fundamental Matrix Estimation for Uncalibrated Cameras 未校准相机的五点基本矩阵估计 | |
| 350.FlipDial: A Generative Model for Two-Way Visual Dialogue FlipDial：双向视觉对话的生成模型 |
| 论文 | 概要 |
|---|---|
| 351.Flow Guided Recurrent Neural Encoder for Video Salient Object Detection 流导向的递归神经编码器，用于视频显着目标检测 | |
| 352.Focal Visual-Text Attention for Visual Question Answering 视觉问题解答的焦点视觉文本注意 | |
| 353.Focus Manipulation Detection via Photometric Histogram Analysis 通过光度直方图分析进行焦点操纵检测 | |
| 354.FoldingNet: Point Cloud Auto-Encoder via Deep Grid Deformation FoldingNet：通过深层网格变形的点云自动编码器 | |
| 355.Fooling Vision and Language Models Despite Localization and Attention Mechanism 尽管存在本地化和注意力机制，但仍会愚弄视觉和语言模型 | |
| 356.FOTS: Fast Oriented Text Spotting With a Unified Network FOTS：使用统一网络快速定位文本 | |
| 357.Frame-Recurrent Video Super-Resolution 帧循环视频超分辨率 | |
| 358.Free Supervision From Video Games 电子游戏免费监督 | |
| 359.From Lifestyle Vlogs to Everyday Interactions 从生活时尚博客到日常互动 | |
| 360.From Source to Target and Back: Symmetric Bi-Directional Adaptive GAN 从源到目标再到目标：对称双向自适应GAN | |
| 361.Frustum PointNets for 3D Object Detection From RGB-D Data 用于从RGB-D数据进行3D对象检测的Frustum PointNets | |
| 362.FSRNet: End-to-End Learning Face Super-Resolution With Facial Priors FSRNet：具有面部先验的端到端学习面孔超分辨率 | |
| 363.Fully Convolutional Adaptation Networks for Semantic Segmentation 用于语义分割的全卷积自适应网络 | |
| 364.Functional Map of the World 世界功能地图 | |
| 365.Fusing Crowd Density Maps and Visual Object Trackers for People Tracking in Crowd Scenes 融合人群密度图和视觉对象跟踪器以在人群场景中进行人跟踪 | |
| 366.Future Frame Prediction for Anomaly Detection - A New Baseline 异常检测的未来帧预测-新基准 | |
| 367.Future Person Localization in First-Person Videos 第一人称视频中的未来人本地化 | |
| 368.GAGAN: Geometry-Aware Generative Adversarial Networks GAGAN：几何感知生成对抗网络 | |
| 369.GANerated Hands for Real-Time 3D Hand Tracking From Monocular RGB 用于单眼RGB的实时3D手跟踪的分层手 | |
| 370.Gated Fusion Network for Single Image Dehazing 门控融合网络用于单图像去雾 | |
| 371.Gaze Prediction in Dynamic 360deg Immersive Videos 动态360度沉浸式视频中的注视预测 | |
| 372.Generalized Zero-Shot Learning via Synthesized Examples 通过综合实例进行广义零枪学习 | |
| 373.Generate to Adapt: Aligning Domains Using Generative Adversarial Networks 生成以适应：使用生成对抗网络调整域 | |
| 374.Generating a Fusion Image: One’s Identity and Another’s Shape 生成融合图像：一个人的身份和另一个人的形状 | |
| 375.Generating Synthetic X-Ray Images of a Person From the Surface Geometry 从表面几何形状生成人的合成X射线图像 | |
| 376.Generative Adversarial Image Synthesis With Decision Tree Latent Controller 决策树潜在控制器的对抗式生成图像综合 | |
| 377.Generative Adversarial Learning Towards Fast Weakly Supervised Detection 生成对抗性学习，实现快速弱监督检测 | |
| 378.Generative Adversarial Perturbations 生成对抗性扰动 | |
| 379.Generative Image Inpainting With Contextual Attention 具有上下文注意的生成图像修复 | |
| 380.Generative Modeling Using the Sliced Wasserstein Distance 使用切片Wasserstein距离进行生成建模 | |
| 381.Geometric Multi-Model Fitting With a Convex Relaxation Algorithm 凸松弛算法进行几何多模型拟合 | |
| 382.Geometric Robustness of Deep Networks: Analysis and Improvement 深度网络的几何鲁棒性：分析和改进 | |
| 383.Geometry Aware Constrained Optimization Techniques for Deep Learning 深度学习的几何感知约束优化技术 | |
| 384.Geometry-Aware Deep Network for Single-Image Novel View Synthesis 用于单图像新颖视图合成的几何感知深度网络 | |
| 385.Geometry-Aware Learning of Maps for Camera Localization 用于相机定位的地图的几何感知学习 | |
| 386.Geometry-Aware Network for Non-Rigid Shape Prediction From a Single View 从单个视图进行非刚性形状预测的几何感知网络 | |
| 387.Geometry-Aware Scene Text Detection With Instance Transformation Network 具有实例转换网络的几何感知场景文本检测 | |
| 388.Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning 几何指导的卷积神经网络用于自指导视频表示学习 | |
| 389.GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation GeoNet：用于联合深度和表面法线估计的几何神经网络 | |
| 390.GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose GeoNet：密集深度，光流和相机姿势的无监督学习 | |
| 391.Gesture Recognition: Focus on the Hands 手势识别：专注于手 | |
| 392.Gibson Env: Real-World Perception for Embodied Agents 吉布森环境（Gibson Env）：现实世界对特工的看法 | |
| 393.Glimpse Clouds: Human Activity Recognition From Unstructured Feature Points 瞥见云：来自非结构化特征点的人类活动识别 | |
| 394.Globally Optimal Inlier Set Maximization for Atlanta Frame Estimation 亚特兰大帧估计的全局最优Inlier集最大化 | |
| 395.Global Versus Localized Generative Adversarial Nets 全球与本地化生成对抗网 | |
| 396.Going From Image to Video Saliency: Augmenting Image Salience With Dynamic Attentional Push 从图像到视频显着性：通过动态注意力推送来增强图像显着性 | |
| 397.Good View Hunting: Learning Photo Composition From Dense View Pairs 良好的视野狩猎：从密集的视野对中学习照片构图 | |
| 398.GraphBit: Bitwise Interaction Mining via Deep Reinforcement Learning GraphBit：通过深度强化学习进行按位交互挖掘 | |
| 399.Graph-Cut RANSAC 图切RANSAC | |
| 400.Grounding Referring Expressions in Images by Variational Context 通过变体上下文使图像中的指称表达接地 |
| 论文 | 概要 |
|---|---|
| 401.GroupCap: Group-Based Image Captioning With Structured Relevance and Diversity Constraints GroupCap：具有结构相关性和多样性约束的基于组的图像字幕 | |
| 402.Group Consistent Similarity Learning via Deep CRF for Person Re-Identification 通过深度CRF进行群体一致性相似性学习以进行人员重新识别 | |
| 403.Guided Proofreading of Automatic Segmentations for Connectomics Connectomics自动细分的指导性校对 | |
| 404.Guide Me: Interacting With Deep Networks 指导我：与深度网络互动 | |
| 405.GVCNN: Group-View Convolutional Neural Networks for 3D Shape Recognition GVCNN：用于3D形状识别的组视图卷积神经网络 | |
| 406.Hallucinated-IQA: No-Reference Image Quality Assessment via Adversarial Learning 幻觉IQA：通过对抗学习进行无参考图像质量评估 | |
| 407.Hand PointNet: 3D Hand Pose Estimation Using Point Sets Hand PointNet：使用点集的3D手姿估计 | |
| 408.Harmonious Attention Network for Person Re-Identification 重新识别人的和谐注意网络 | |
| 409.HashGAN: Deep Learning to Hash With Pair Conditional Wasserstein GAN HashGAN：深度学习与有条件的Wasserstein GAN配对 | |
| 410.Hashing as Tie-Aware Learning to Rank 散列为领带感知学习排名 | |
| 411.HATS: Histograms of Averaged Time Surfaces for Robust Event-Based Object Classification HATS：鲁棒的基于事件的对象分类的平均时间表面直方图 | |
| 412.Hierarchical Novelty Detection for Visual Object Recognition 视觉对象识别的层次新颖性检测 | |
| 413.Hierarchical Recurrent Attention Networks for Structured Online Maps 结构化在线地图的分层递归注意网络 | |
| 414.High-Order Tensor Regularization With Application to Attribute Ranking 高阶张量正则化及其在属性排序中的应用 | |
| 415.High Performance Visual Tracking With Siamese Region Proposal Network 连体区域提案网络的高性能视觉跟踪 | |
| 416.High-Resolution Image Synthesis and Semantic Manipulation With Conditional GANs 有条件GAN的高分辨率图像合成和语义处理 | |
| 417.High-Speed Tracking With Multi-Kernel Correlation Filters 利用多核相关滤波器进行高速跟踪 | |
| 418.HSA-RNN: Hierarchical Structure-Adaptive RNN for Video Summarization HSA-RNN：用于视频汇总的分层结构自适应RNN | |
| 419.Human Appearance Transfer 人的外观转移 | |
| 420.Human-Centric Indoor Scene Synthesis Using Stochastic Grammar 基于随机语法的以人为中心的室内场景合成 | |
| 421.Human Pose Estimation With Parsing Induced Learner 解析诱导学习者的人体姿势估计 | |
| 422.Human Semantic Parsing for Person Re-Identification 用于人员重新识别的人类语义解析 | |
| 423.Hybrid Camera Pose Estimation 混合相机姿势估计 | |
| 424.HydraNets: Specialized Dynamic Architectures for Efficient Inference HydraNets：高效推理的专用动态架构 | |
| 425.Hyperparameter Optimization for Tracking With Continuous Deep Q-Learning 连续深度Q学习的超参数优化跟踪 | |
| 426.ICE-BA: Incremental, Consistent and Efficient Bundle Adjustment for Visual-Inertial SLAM ICE-BA：视觉惯性SLAM的增量，一致和高效的捆绑包调整 | |
| 427.Illuminant Spectra-Based Source Separation Using Flash Photography 使用闪光灯摄影的基于光谱的光源分离 | |
| 428.Im2Flow: Motion Hallucination From Static Images for Action Recognition Im2Flow：从静态图像进行动作幻觉以进行动作识别 | |
| 429.Im2Pano3D: Extrapolating 360deg Structure and Semantics Beyond the Field of View Im2Pano3D：超越视野，外推360度结构和语义 | |
| 430.Im2Struct: Recovering 3D Shape Structure From a Single RGB Image Im2Struct：从单个RGB图像中恢复3D形状结构 | |
| 431.Image Blind Denoising With Generative Adversarial Network Based Noise Modeling 基于生成对抗网络的噪声建模的图像盲去噪 | |
| 432.Image Collection Pop-Up: 3D Reconstruction and Clustering of Rigid and Non-Rigid Categories 图像集合弹出窗口：刚性和非刚性类别的3D重构和聚类 | |
| 433.Image Correction via Deep Reciprocating HDR Transformation 通过深度往复HDR变换进行图像校正 | |
| 434.Image Generation From Scene Graphs 从场景图生成图像 | |
| 435.Image-Image Domain Adaptation With Preserved Self-Similarity and Domain-Dissimilarity for Person Re-Identification 保留人的自我相似性和域相似性的图像-图像域自适应 | |
| 436.Image Restoration by Estimating Frequency Distribution of Local Patches 通过估计局部补丁的频率分布来恢复图像 | |
| 437.Image Super-Resolution via Dual-State Recurrent Networks 通过双状态循环网络实现图像超分辨率 | |
| 438.Image to Image Translation for Domain Adaptation 图像到图像翻译以进行域自适应 | |
| 439.Importance Weighted Adversarial Nets for Partial Domain Adaptation 局部域自适应的重要性加权对抗网 | |
| 440.Improved Fusion of Visual and Language Representations by Dense Symmetric Co-Attention for Visual Question Answering 密集的对称共同注意对视觉问题的回答，改善了视觉和语言表示的融合 | |
| 441.Improved Lossy Image Compression With Priming and Spatially Adaptive Bit Rates for Recurrent Networks 面向递归网络的具有启动和空间自适应位速率的改进的有损图像压缩 | |
| 442.Improvements to Context Based Self-Supervised Learning 基于上下文的自我监督学习的改进 | |
| 443.Improving Color Reproduction Accuracy on Cameras 提高相机的色彩还原精度 | |
| 444.Improving Landmark Localization With Semi-Supervised Learning 通过半监督学习改善地标本地化 | |
| 445.Improving Object Localization With Fitness NMS and Bounded IoU Loss 使用Fitness NMS和有限的IoU损失改善对象定位 | |
| 446.Improving Occlusion and Hard Negative Handling for Single-Stage Pedestrian Detectors 改善单阶段行人探测器的遮挡和硬负处理 | |
| 447.Independently Recurrent Neural Network (IndRNN): Building a Longer and Deeper RNN 独立循环神经网络（IndRNN）：构建更长更深的RNN | |
| 448.Indoor RGB-D Compass From a Single Line and Plane 单线和平面的室内RGB-D指南针 | |
| 449.Inference in Higher Order MRF-MAP Problems With Small and Large Cliques 带有小集团的高阶MRF-MAP问题的推论 | |
| 450.Inferring Light Fields From Shadows 从阴影推断光场 |
| 论文 | 概要 |
|---|---|
| 451.Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis 推理语义布局以实现文本到图像的分层合成 | |
| 452.Inferring Shared Attention in Social Scene Videos 推断社交场景视频中的共享注意力 | |
| 453.InLoc: Indoor Visual Localization With Dense Matching and View Synthesis InLoc：具有密集匹配和视图综合的室内视觉本地化 | |
| 454.In-Place Activated BatchNorm for Memory-Optimized Training of DNNs 就地激活的BatchNorm，用于DNN的内存优化训练 | |
| 455.Instance Embedding Transfer to Unsupervised Video Object Segmentation 实例嵌入转移到无监督视频对象分割 | |
| 456.Interactive Image Segmentation With Latent Diversity 具有潜在多样性的交互式图像分割 | |
| 457.Interleaved Structured Sparse Convolutional Neural Networks 交错结构的稀疏卷积神经网络 | |
| 458.Interpretable Convolutional Neural Networks 可解释的卷积神经网络 | |
| 459.Interpretable Video Captioning via Trajectory Structured Localization 通过轨迹结构化本地化可解释的视频字幕 | |
| 460.Interpret Neural Networks by Identifying Critical Data Routing Paths 通过识别关键数据路由路径来解释神经网络 | |
| 461.Intrinsic Image Transformation via Scale Space Decomposition 通过尺度空间分解的本征图像变换 | |
| 462.Inverse Composition Discriminative Optimization for Point Cloud Registration 点云配准的逆组合判别优化 | |
| 463.InverseFaceNet: Deep Monocular Inverse Face Rendering InverseFaceNet：深单目反面渲染 | |
| 464.IQA: Visual Question Answering in Interactive Environments IQA：交互环境中的视觉问题解答 | |
| 465.ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing ISTA-Net：基于可解释性优化的深度网络，用于图像压缩传感 | |
| 466.Iterative Learning With Open-Set Noisy Labels 开放式嘈杂标签的迭代学习 | |
| 467.Iterative Visual Reasoning Beyond Convolutions 超越卷积的迭代视觉推理 | |
| 468.IVQA: Inverse Visual Question Answering IVQA：逆向视觉问答 | |
| 469.Jerk-Aware Video Acceleration Magnification 挺举感知视频加速倍率 | |
| 470.Joint Cuts and Matching of Partitions in One Graph 一幅图中的联合切割和分区匹配 | |
| 471.Jointly Localizing and Describing Events for Dense Video Captioning 联合本地化和描述用于密集视频字幕的事件 | |
| 472.Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation 联合优化数据增强和网络培训：人体姿势估计中的对抗性数据增强 | |
| 473.Joint Optimization Framework for Learning With Noisy Labels 带有噪音标签的联合优化学习框架 | |
| 474.Joint Pose and Expression Modeling for Facial Expression Recognition 面部表情识别的联合姿势和表情建模 | |
| 475.Kernelized Subspace Pooling for Deep Local Descriptors 深度本地描述符的内核化子空间池 | |
| 476.KIPPI: KInetic Polygonal Partitioning of Images KIPPI：图像的运动多边形分割 | |
| 477.Knowledge Aided Consistency for Weakly Supervised Phrase Grounding 弱监督短语接地的知识辅助一致性 | |
| 478.Label Denoising Adversarial Network (LDAN) for Inverse Lighting of Faces 用于面部反照的标签去噪对抗网络（LDAN） | |
| 479.LAMV: Learning to Align and Match Videos With Kernelized Temporal Layers LAMV：学习将视频与内核时间层对齐和匹配 | |
| 480.Language-Based Image Editing With Recurrent Attentive Models 基于循环注意力模型的基于语言的图像编辑 | |
| 481.Large-Scale Distance Metric Learning With Uncertainty 不确定性的大规模远程度量学习 | |
| 482.Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning 大规模细粒度分类和特定领域转移学习 | |
| 483.Large-Scale Point Cloud Semantic Segmentation With Superpoint Graphs 超点图的大规模点云语义分割 | |
| 484.Latent RANSAC 潜在的RANSAC | |
| 485.LayoutNet: Reconstructing the 3D Room Layout From a Single RGB Image LayoutNet：从单个RGB图像重建3D房间布局 | |
| 486.LDMNet: Low Dimensional Manifold Regularized Neural Networks LDMNet：低维流形正则化神经网络 | |
| 487.Lean Multiclass Crowdsourcing 精益多类众包 | |
| 488.Learned Shape-Tailored Descriptors for Segmentation 习得的形状定制描述符用于细分 | |
| 489.Learning 3D Shape Completion From Laser Scan Data With Weak Supervision 通过弱监督从激光扫描数据中学习3D形状完成 | |
| 490.Learning a Complete Image Indexing Pipeline 学习完整的图像索引管道 | |
| 491.Learning a Discriminative Feature Network for Semantic Segmentation 学习用于语义分割的判别特征网络 | |
| 492.Learning a Discriminative Filter Bank Within a CNN for Fine-Grained Recognition 学习CNN中的判别式滤波器组以进行细粒度识别 | |
| 493.Learning a Discriminative Prior for Blind Image Deblurring 学习判别先验盲图像去模糊 | |
| 494.Learning and Using the Arrow of Time 学习和使用时间之箭 | |
| 495.Learning Answer Embeddings for Visual Question Answering 学习视觉视觉答案的答案嵌入 | |
| 496.Learning a Single Convolutional Super-Resolution Network for Multiple Degradations 学习单个卷积超分辨率网络以进行多次降级 | |
| 497.Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking 学习注意力：残余注意力连体网络，用于高性能在线视觉跟踪 | |
| 498.Learning Attribute Representations With Localization for Flexible Fashion Search 通过本地化学习属性表示以实现灵活的时尚搜索 | |
| 499.Learning by Asking Questions 提问学习 | |
| 500.Learning Compact Recurrent Neural Networks With Block-Term Tensor Decomposition 通过块期张量分解学习紧凑型递归神经网络 |
| 论文 | 概要 |
|---|---|
| 501.Learning Compositional Visual Concepts With Mutual Consistency 相互一致地学习构图视觉概念 | |
| 502.Learning Compressible 360deg Video Isomers 学习可压缩的360deg视频异构体 | |
| 503.“Learning-Compression” Algorithms for Neural Net Pruning 神经网络修剪的“学习-压缩”算法 | |
| 504.Learning Convolutional Networks for Content-Weighted Image Compression 学习卷积网络进行内容加权图像压缩 | |
| 505.Learning Deep Descriptors With Scale-Aware Triplet Networks 使用可感知规模的三重态网络学习深度描述符 | |
| 506.Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision 学习深度模型进行面部反欺骗：二进制或辅助监督 | |
| 507.Learning Deep Sketch Abstraction 学习深度素描抽象 | |
| 508.Learning Deep Structured Active Contours End-to-End 端到端学习深度结构化活动轮廓 | |
| 509.Learning Depth From Monocular Videos Using Direct Methods 使用直接方法从单眼视频中学习深度 | |
| 510.Learning Descriptor Networks for 3D Shape Synthesis and Analysis 用于3D形状合成和分析的学习描述符网络 | |
| 511.Learning Distributions of Shape Trajectories From Longitudinal Datasets: A Hierarchical Model on a Manifold of Diffeomorphisms 从纵向数据集学习形状轨迹的分布：Diffeomorphisms流形的层次模型。 | |
| 512.Learning Dual Convolutional Neural Networks for Low-Level Vision 学习双卷积神经网络以实现低视力 | |
| 513.Learning Face Age Progression: A Pyramid Architecture of GANs 学习面部年龄发展：GAN的金字塔体系结构 | |
| 514.Learning Facial Action Units From Web Images With Scalable Weakly Supervised Clustering 通过可扩展的弱监督聚类从Web图像中学习面部动作单元 | |
| 515.Learning for Disparity Estimation Through Feature Constancy 通过特征恒定学习差异估计 | |
| 516.Learning From Millions of 3D Scans for Large-Scale 3D Face Recognition 从数百万的3D扫描中学习以进行大规模3D人脸识别 | |
| 517.Learning From Noisy Web Data With Category-Level Supervision 通过类别级监督从嘈杂的Web数据中学习 | |
| 518.Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation 从合成数据中学习：解决语义语义分割的域移位 | |
| 519.Learning Generative ConvNets via Multi-Grid Modeling and Sampling 通过多网格建模和采样学习生成式ConvNet | |
| 520.Learning Globally Optimized Object Detector via Policy Gradient 通过策略梯度学习全局优化的对象检测器 | |
| 521.Learning Intelligent Dialogs for Bounding Box Annotation 学习边界框注释的智能对话框 | |
| 522.Learning Intrinsic Image Decomposition From Watching the World 从观看世界中学习内在的图像分解 | |
| 523.Learning Latent Super-Events to Detect Multiple Activities in Videos 学习潜在的超级事件以检测视频中的多个活动 | |
| 524.Learning Less Is More - 6D Camera Localization via 3D Surface Regression 学会少即是多-通过3D表面回归实现6D相机本地化 | |
| 525.Learning Markov Clustering Networks for Scene Text Detection 学习用于场景文本检测的马尔可夫聚类网络 | |
| 526.Learning Monocular 3D Human Pose Estimation From Multi-View Images 从多视图图像中学习单眼3D人类姿势估计 | |
| 527.Learning Multi-Instance Enriched Image Representations via Non-Greedy Ratio Maximization of the l1-Norm Distances 通过l1-Norm距离的非贪心比最大化学习多实例富集图像表示 | |
| 528.Learning Patch Reconstructability for Accelerating Multi-View Stereo 学习补丁可重构性，以加速多视图立体声 | |
| 529.Learning Pixel-Level Semantic Affinity With Image-Level Supervision for Weakly Supervised Semantic Segmentation 通过图像级监督学习像素级语义亲和度以实现弱监督语义分割 | |
| 530.Learning Pose Specific Representations by Predicting Different Views 通过预测不同的观点来学习姿势特定表示 | |
| 531.Learning Rich Features for Image Manipulation Detection 学习丰富的图像操纵检测功能 | |
| 532.Learning Semantic Concepts and Order for Image and Sentence Matching 学习语义概念和图像和句子匹配的顺序 | |
| 533.Learning Spatial-Aware Regressions for Visual Tracking 学习用于视觉跟踪的空间感知回归 | |
| 534.Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking 学习时空正则化相关滤波器以进行视觉跟踪 | |
| 535.Learning Steerable Filters for Rotation Equivariant CNNs 学习旋转等变CNN的可控滤波器 | |
| 536.Learning Strict Identity Mappings in Deep Residual Networks 在深度残差网络中学习严格的身份映射 | |
| 537.Learning Structure and Strength of CNN Filters for Small Sample Size Training 小样本量训练的CNN滤波器的学习结构和强度 | |
| 538.Learning Superpixels With Segmentation-Aware Affinity Loss 通过分段感知的亲和力损失学习超像素 | |
| 539.Learning Time_Memory-Efficient Deep Architectures With Budgeted Super Networks 通过预算的超级网络学习时间_内存高效的深度架构 | |
| 540.Learning to Act Properly: Predicting and Explaining Affordances From Images 学习正确采取行动：预测和解释图像中的负担 | |
| 541.Learning to Adapt Structured Output Space for Semantic Segmentation 学习适应结构化输出空间进行语义分割 | |
| 542.Learning to Compare: Relation Network for Few-Shot Learning 学习比较：很少学习的关系网络 | |
| 543.Learning to Detect Features in Texture Images 学习检测纹理图像中的特征 | |
| 544.Learning to Estimate 3D Human Pose and Shape From a Single Color Image 学习从单色图像估计3D人类姿势和形状 | |
| 545.Learning to Evaluate Image Captioning 学习评估图像字幕 | |
| 546.Learning to Extract a Video Sequence From a Single Motion-Blurred Image 学习从单个运动模糊图像中提取视频序列 | |
| 547.Learning to Find Good Correspondences 学习寻找良好的对应关系 | |
| 548.Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networks 学习使用多阶段动态生成对抗网络生成延时视频 | |
| 549.Learning to Localize Sound Source in Visual Scenes 学习在视觉场景中定位声源 | |
| 550.Learning to Look Around: Intelligently Exploring Unseen Environments for Unknown Tasks 学习环顾四周：智能探索未知任务未知的环境 |
| 论文 | 概要 |
|---|---|
| 551.Learning to Parse Wireframes in Images of Man-Made Environments 学习解析人造环境图像中的线框 | |
| 552.Learning to Promote Saliency Detectors 学习促进显着性检测器 | |
| 553.Learning to See in the Dark 学习在黑暗中看 | |
| 554.Learning to Segment Every Thing 学会分割一切 | |
| 555.Learning to Sketch With Shortcut Cycle Consistency 学习以快捷的周期一致性进行素描 | |
| 556.Learning to Understand Image Blur 学习理解图像模糊 | |
| 557.Learning Transferable Architectures for Scalable Image Recognition 学习可扩展的体系结构以实现可扩展的图像识别 | |
| 558.Learning Visual Knowledge Memory Networks for Visual Question Answering 学习视觉知识记忆网络以进行视觉问答 | |
| 559.Left-Right Comparative Recurrent Model for Stereo Matching 立体声匹配的左右比较递归模型 | |
| 560.LEGO: Learning Edge With Geometry All at Once by Watching Videos 乐高：通过观看视频一次学习几何的优势 | |
| 561.Leveraging Unlabeled Data for Crowd Counting by Learning to Rank 通过学习排名利用未标记的数据进行人群计数 | |
| 562.LiDAR-Video Driving Dataset: Learning Driving Policies Effectively LiDAR视频驾驶数据集：有效学习驾驶策略 | |
| 563.Light Field Intrinsics With a Deep Encoder-Decoder Network 具有深层编码器-解码器网络的光场本征 | |
| 564.Lightweight Probabilistic Deep Networks 轻型概率深度网络 | |
| 565.LIME: Live Intrinsic Material Estimation LIME：实时内在材料估计 | |
| 566.Link and Code: Fast Indexing With Graphs and Compact Regression Codes 链接和代码：使用图形和紧凑回归代码进行快速索引 | |
| 567.Lions and Tigers and Bears: Capturing Non-Rigid, 3D, Articulated Shape From Images 狮子和老虎与熊：从图像中捕获非刚性，3D，关节形状 | |
| 568.LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation LiteFlowNet：用于光流估计的轻量级卷积神经网络 | |
| 569.Local and Global Optimization Techniques in Graph-Based Clustering 基于图的聚类中的局部和全局优化技术 | |
| 570.Local Descriptors Optimized for Average Precision 优化本地描述符以实现平均精度 | |
| 571.Logo Synthesis and Manipulation With Clustered Generative Adversarial Networks 聚类生成对抗网络的徽标合成和操纵 | |
| 572.Long-Term On-Board Prediction of People in Traffic Scenes Under Uncertainty 不确定情况下交通场景中人员的长期车载预测 | |
| 573.Look at Boundary: A Boundary-Aware Face Alignment Algorithm 看边界：边界感知的人脸对齐算法 | |
| 574.Look, Imagine and Match: Improving Textual-Visual Cross-Modal Retrieval With Generative Models 外观，想象和匹配：使用生成模型改进文本视觉跨模态检索 | |
| 575.Lose the Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion 失去视野：通过隐式Singram完成有限角度CT重建 | |
| 576.Low-Latency Video Semantic Segmentation 低延迟视频语义分割 | |
| 577.Low-Shot Learning From Imaginary Data 虚幻数据的低速学习 | |
| 578.Low-Shot Learning With Imprinted Weights 带有权重的低速学习 | |
| 579.Low-Shot Learning With Large-Scale Diffusion 大规模扩散的低射学习 | |
| 580.LSTM Pose Machines LSTM姿势机 | |
| 581.M3: Multimodal Memory Modelling for Video Captioning M3：用于视频字幕的多模式内存建模 | |
| 582.Making Convolutional Networks Recurrent for Visual Sequence Learning 使卷积网络循环进行视觉序列学习 | |
| 583.Manifold Learning in Quotient Spaces 商空间中的流形学习 | |
| 584.MapNet: An Allocentric Spatial Memory for Mapping Environments MapNet：映射环境的同心圆空间内存 | |
| 585.Mask-Guided Contrastive Attention Model for Person Re-Identification 面罩引导的对比注意模型用于人员重新识别 | |
| 586.MaskLab: Instance Segmentation by Refining Object Detection With Semantic and Direction Features MaskLab：通过语义和方向特征完善对象检测来实现实例分割 | |
| 587.Matching Adversarial Networks 匹配的对抗网络 | |
| 588.Matching Pixels Using Co-Occurrence Statistics 使用共现统计匹配像素 | |
| 589.Matryoshka Networks: Predicting 3D Geometry via Nested Shape Layers Matryoshka Networks：通过嵌套形状层预测3D几何 | |
| 590.MAttNet: Modular Attention Network for Referring Expression Comprehension MAttNet：用于引用表达理解的模块化注意网络 | |
| 591.Maximum Classifier Discrepancy for Unsupervised Domain Adaptation 无监督域自适应的最大分类器差异 | |
| 592.Mean-Variance Loss for Deep Age Estimation From a Face 从脸部进行深度估计的均值方差损失 | |
| 593.MegaDepth: Learning Single-View Depth Prediction From Internet Photos MegaDepth：从互联网照片中学习单视图深度预测 | |
| 594.MegDet: A Large Mini-Batch Object Detector MegDet：大型小批量物体检测器 | |
| 595.Memory Based Online Learning of Deep Representations From Video Streams 基于内存的视频流深度表示在线学习 | |
| 596.Memory Matching Networks for One-Shot Image Recognition 一键式图像识别的内存匹配网络 | |
| 597.Mesoscopic Facial Geometry Inference Using Deep Neural Networks 使用深层神经网络的介观面部几何推理 | |
| 598.MiCT: Mixed 3D_2D Convolutional Tube for Human Action Recognition MiCT：用于人类动作识别的混合3D_2D卷积管 | |
| 599.Min-Entropy Latent Model for Weakly Supervised Object Detection 弱熵目标检测的最小熵潜模型 | |
| 600.Mining on Manifolds: Metric Learning Without Labels 流形上的挖掘：无标签的公制学习 |
| 论文 | 概要 |
|---|---|
| 601.Mining Point Cloud Local Structures by Kernel Correlation and Graph Pooling 基于核相关和图池的挖掘点云局部结构 | |
| 602.Missing Slice Recovery for Tensors Using a Low-Rank Model in Embedded Space 在嵌入式空间中使用低秩模型进行张量缺失切片恢复 | |
| 603.Mix and Match Networks: Encoder-Decoder Alignment for Zero-Pair Image Translation 混合和匹配网络：零对图像转换的编码器-解码器对准 | |
| 604.MobileNetV2: Inverted Residuals and Linear Bottlenecks MobileNetV2：残差和线性瓶颈 | |
| 605.Mobile Video Object Detection With Temporally-Aware Feature Maps 具有临时感知特征图的移动视频对象检测 | |
| 606.MoCoGAN: Decomposing Motion and Content for Video Generation MoCoGAN：分解运动和内容以生成视频 | |
| 607.Modeling Facial Geometry Using Compositional VAEs 使用合成VAE对面部几何建模 | |
| 608.Modifying Non-Local Variations Across Multiple Views 跨多个视图修改非局部变化 | |
| 609.Modulated Convolutional Networks 调制卷积网络 | |
| 610.MoNet: Deep Motion Exploitation for Video Object Segmentation MoNet：用于视频对象分割的深度运动开发 | |
| 611.MoNet: Moments Embedding Network MoNet：时刻嵌入网络 | |
| 612.Monocular 3D Pose and Shape Estimation of Multiple People in Natural Scenes - The Importance of Multiple Scene Constraints 自然场景中多人的单眼3D姿势和形状估计-多场景约束的重要性 | |
| 613.Monocular Relative Depth Perception With Web Stereo Data Supervision Web立体声数据监控的单眼相对深度感知 | |
| 614.MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks MorphNet：深度网络的快速，简单的资源受限结构学习 | |
| 615.Motion-Appearance Co-Memory Networks for Video Question Answering 运动外观协同存储网络，用于视频问答 | |
| 616.Motion-Guided Cascaded Refinement Network for Video Object Segmentation 运动引导级联细化网络的视频对象分割 | |
| 617.Motion Segmentation by Exploiting Complementary Geometric Models 利用互补几何模型进行运动分割 | |
| 618.MovieGraphs: Towards Understanding Human-Centric Situations From Videos MovieGraphs：通过视频了解以人为中心的情况 | |
| 619.Multi-Agent Diverse Generative Adversarial Networks 多智能体多元化生成对抗网络 | |
| 620.Multi-Cell Detection and Classification Using a Generative Convolutional Model 使用生成卷积模型进行多细胞检测和分类 | |
| 621.Multi-Content GAN for Few-Shot Font Style Transfer 多内容GAN，可进行少量字体转换 | |
| 622.Multi-Cue Correlation Filters for Robust Visual Tracking 多线索相关滤波器可实现强大的视觉跟踪 | |
| 623.Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning 基于弱监督学习的多标签分类，目标检测和语义分割的多证据过滤与融合 | |
| 624.Multi-Frame Quality Enhancement for Compressed Video 压缩视频的多帧质量增强 | |
| 625.Multi-Image Semantic Matching by Mining Consistent Features 挖掘一致特征的多图像语义匹配 | |
| 626.Multi-Label Zero-Shot Learning With Structured Knowledge Graphs 具有结构化知识图的多标签零射击学习 | |
| 627.Multi-Level Factorisation Net for Person Re-Identification 用于人员重新识别的多层次分解网络 | |
| 628.Multi-Level Fusion Based 3D Object Detection From Monocular Images 基于多级融合的单眼图像3D目标检测 | |
| 629.Multimodal Explanations: Justifying Decisions and Pointing to the Evidence 多式联运的解释：做出合理的决定并指向证据 | |
| 630.Multimodal Visual Concept Learning With Weakly Supervised Techniques 弱监督技术的多模式视觉概念学习 | |
| 631.Multi-Oriented Scene Text Detection via Corner Localization and Region Segmentation 通过角点定位和区域分割的多方位场景文本检测 | |
| 632.Multiple Granularity Group Interaction Prediction 多粒度群相互作用预测 | |
| 633.Multi-Scale Location-Aware Kernel Representation for Object Detection 用于对象检测的多尺度位置感知内核表示 | |
| 634.Multi-Scale Weighted Nuclear Norm Image Restoration 多尺度加权核规范图像复原 | |
| 635.Multi-Shot Pedestrian Re-Identification via Sequential Decision Making 通过顺序决策进行多步行人重新识别 | |
| 636.Multispectral Image Intrinsic Decomposition via Subspace Constraint 通过子空间约束进行多光谱图像固有分解 | |
| 637.Multistage Adversarial Losses for Pose-Based Human Image Synthesis 基于姿势的人体图像合成的多阶段对抗性损失 | |
| 638.Multi-Task Adversarial Network for Disentangled Feature Learning 多任务对抗网络的融合特征学习 | |
| 639.Multi-Task Learning by Maximizing Statistical Dependence 通过最大化统计依赖性进行多任务学习 | |
| 640.Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics 使用不确定性权衡场景几何和语义损失的多任务学习 | |
| 641.Multi-View Consistency as Supervisory Signal for Learning Shape and Pose Prediction 多视图一致性作为学习形状和姿势预测的监督信号 | |
| 642.Multi-View Harmonized Bilinear Network for 3D Object Recognition 用于3D对象识别的多视图协调双线性网络 | |
| 643.MX-LSTM: Mixing Tracklets and Vislets to Jointly Forecast Trajectories and Head Poses MX-LSTM：将小轨迹和小片段混合以共同预测轨迹和头部姿势 | |
| 644.NAG: Network for Adversary Generation NAG：对手生成网络 | |
| 645.Natural and Effective Obfuscation by Head Inpainting 通过头部绘画进行自然而有效的混淆 | |
| 646.NestedNet: Learning Nested Sparse Structures in Deep Neural Networks NestedNet：在深度神经网络中学习嵌套的稀疏结构 | |
| 647.Net2Vec: Quantifying and Explaining How Concepts Are Encoded by Filters in Deep Neural Networks Net2Vec：量化和解释深度神经网络中的过滤器如何编码概念 | |
| 648.Neural 3D Mesh Renderer 神经3D网格渲染器 | |
| 649.Neural Baby Talk 神经婴儿谈话 | |
| 650.Neural Kinematic Networks for Unsupervised Motion Retargetting 神经运动网络的无监督运动重定向 |
| 论文 | 概要 |
|---|---|
| 651.Neural Motifs: Scene Graph Parsing With Global Context 神经图案：具有全局上下文的场景图解析 | |
| 652.NeuralNetwork-Viterbi: A Framework for Weakly Supervised Video Learning NeuralNetwork-Viterbi：弱监督视频学习的框架 | |
| 653.Neural Sign Language Translation 神经手语翻译 | |
| 654.Neural Style Transfer via Meta Networks 通过元网络进行神经风格传递 | |
| 655.NISP: Pruning Networks Using Neuron Importance Score Propagation NISP：使用神经元重要性分数传播修剪网络 | |
| 656.Non-Blind Deblurring: Handling Kernel Uncertainty With CNNs 非盲去模糊：使用CNN处理内核不确定性 | |
| 657.Nonlinear 3D Face Morphable Model 非线性3D人脸可变形模型 | |
| 658.Non-Linear Temporal Subspace Representations for Activity Recognition 用于活动识别的非线性时间子空间表示 | |
| 659.Nonlocal Low-Rank Tensor Factor Analysis for Image Restoration 用于图像复原的非局部低秩张量因子分析 | |
| 660.Non-Local Neural Networks 非局部神经网络 | |
| 661.Normalized Cut Loss for Weakly-Supervised CNN Segmentation 弱监督CNN分割的归一化割损 | |
| 662.Now You Shake Me: Towards Automatic 4D Cinema 现在，您让我摇了摇：迈向自动4D电影院 | |
| 663.OATM: Occlusion Aware Template Matching by Consensus Set Maximization OATM：通过共识集最大化来匹配遮挡感知模板 | |
| 664.Object Referring in Videos With Language and Human Gaze 具有语言和人眼注视的视频中的对象引用 | |
| 665.Objects as Context for Detecting Their Semantic Parts 对象作为上下文来检测其语义部分 | |
| 666.Occluded Pedestrian Detection Through Guided Attention in CNNs 在CNN中通过引导注意力进行行人检测 | |
| 667.Occlusion-Aware Rolling Shutter Rectification of 3D Scenes 遮挡感知型3D场景的卷帘式快门矫正 | |
| 668.Occlusion Aware Unsupervised Learning of Optical Flow 遮挡感知光流的无监督学习 | |
| 669.OLE: Orthogonal Low-Rank Embedding - A Plug and Play Geometric Loss for Deep Learning OLE：正交低秩嵌入-深度学习的即插即用几何损失 | |
| 670.One-Shot Action Localization by Learning Sequence Matching Network 通过学习序列匹配网络进行一键式动作定位 | |
| 671.On the Convergence of PatchMatch and Its Variants 关于PatchMatch及其变体的收敛性 | |
| 672.On the Duality Between Retinex and Image Dehazing Retinex与图像去雾之间的对偶 | |
| 673.On the Importance of Label Quality for Semantic Segmentation 标签质量在语义分割中的重要性 | |
| 674.On the Robustness of Semantic Segmentation Models to Adversarial Attacks 语义分割模型对对抗攻击的鲁棒性 | |
| 675.Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition 光流引导功能：用于视频动作识别的快速且鲁棒的运动表示 | |
| 676.Optimal Structured Light a La Carte 最佳结构灯点菜 | |
| 677.Optimizing Filter Size in Convolutional Neural Networks for Facial Action Unit Recognition 卷积神经网络中用于面部动作单元识别的滤波器大小优化 | |
| 678.Optimizing Video Object Detection via a Scale-Time Lattice 通过比例时间格优化视频对象检测 | |
| 679.Ordinal Depth Supervision for 3D Human Pose Estimation 3D人体姿势估计的序数深度监督 | |
| 680.PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning PackNet：通过迭代修剪将多个任务添加到单个网络 | |
| 681.PAD-Net: Multi-Tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing PAD-Net：多任务引导的预测和蒸馏网络，用于同时深度估计和场景解析 | |
| 682.PairedCycleGAN: Asymmetric Style Transfer for Applying and Removing Makeup PairedCycleGAN：不对称样式转移，用于涂抹和去除化妆 | |
| 683.Parallel Attention: A Unified Framework for Visual Object Discovery Through Dialogs and Queries 并行注意：通过对话框和查询发现可视对象的统一框架 | |
| 684.Partially Shared Multi-Task Convolutional Neural Network With Local Constraint for Face Attribute Learning 具有局部约束的部分共享多任务卷积神经网络用于人脸属性学习 | |
| 685.Partial Transfer Learning With Selective Adversarial Networks 选择性对抗网络的部分转移学习 | |
| 686.Path Aggregation Network for Instance Segmentation 用于实例分割的路径聚合网络 | |
| 687.People, Penguins and Petri Dishes: Adapting Object Counting Models to New Visual Domains and Object Types Without Forgetting 人，企鹅和培养皿：在不忘记的情况下将对象计数模型适应新的可视域和对象类型 | |
| 688.Person Re-Identification With Cascaded Pairwise Convolutions 级联成对卷积的人员重新识别 | |
| 689.Person Transfer GAN to Bridge Domain Gap for Person Re-Identification 人员转移GAN到桥接域差距以进行人员重新识别 | |
| 690.Perturbative Neural Networks 摄动神经网络 | |
| 691.PhaseNet for Video Frame Interpolation 用于视频帧插值的PhaseNet | |
| 692.Photographic Text-to-Image Synthesis With a Hierarchically-Nested Adversarial Network 分层嵌套对抗网络的摄影文本到图像合成 | |
| 693.Photometric Stereo in Participating Media Considering Shape-Dependent Forward Scatter 考虑形状依赖性前向散射的参与介质中的光度立体 | |
| 694.PiCANet: Learning Pixel-Wise Contextual Attention for Saliency Detection PiCANet：学习像素性上下文注意以进行显着性检测 | |
| 695.PieAPP: Perceptual Image-Error Assessment Through Pairwise Preference PieAPP：通过成对偏好的感知图像错误评估 | |
| 696.Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling Pix3D：单图像3D形状建模的数据集和方法 | |
| 697.Pixels, Voxels, and Views: A Study of Shape Representations for Single View 3D Object Shape Prediction 像素，体素和视图：单视图3D对象形状预测的形状表示研究 | |
| 698.PIXOR: Real-Time 3D Object Detection From Point Clouds PIXOR：来自点云的实时3D对象检测 | |
| 699.Planar Shape Detection at Structural Scales 结构尺度的平面形状检测 | |
| 700.PlaneNet: Piece-Wise Planar Reconstruction From a Single RGB Image PlaneNet：从单个RGB图像进行明智的平面重建 |
| 论文 | 概要 |
|---|---|
| 701.PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation PointFusion：用于3D边界框估计的深度传感器融合 | |
| 702.PointGrid: A Deep Network for 3D Shape Understanding PointGrid：深入了解3D形状的网络 | |
| 703.PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition PointNetVLAD：基于深度点云的大规模位置识别检索 | |
| 704.Pointwise Convolutional Neural Networks 点向卷积神经网络 | |
| 705.Polarimetric Dense Monocular SLAM 偏振密集单眼SLAM | |
| 706.PoseFlow: A Deep Motion Representation for Understanding Human Behaviors in Videos PoseFlow：用于理解视频中人类行为的深度运动表示 | |
| 707.Pose-Guided Photorealistic Face Rotation 姿势引导的真实感人脸旋转 | |
| 708.pOSE: Pseudo Object Space Error for Initialization-Free Bundle Adjustment pOSE：用于无初始化捆绑调整的伪对象空间错误 | |
| 709.Pose-Robust Face Recognition via Deep Residual Equivariant Mapping 基于深度残差等变映射的姿势鲁棒人脸识别 | |
| 710.PoseTrack: A Benchmark for Human Pose Estimation and Tracking PoseTrack：人体姿势估计和跟踪基准 | |
| 711.Pose Transferrable Person Re-Identification 姿势可转移人员的重新识别 | |
| 712.PoTion: Pose MoTion Representation for Action Recognition PoTion：用于动作识别的姿势运动表示 | |
| 713.PPFNet: Global Context Aware Local Features for Robust 3D Point Matching PPFNet：健壮的3D点匹配的全局上下文感知本地功能 | |
| 714.Practical Block-Wise Neural Network Architecture Generation 实用的块明智神经网络架构生成 | |
| 715.Preserving Semantic Relations for Zero-Shot Learning 保留语义关系以进行零射击学习 | |
| 716.Probabilistic Joint Face-Skull Modelling for Facial Reconstruction 面部重建的概率联合面颅骨模型 | |
| 717.Probabilistic Plant Modeling via Multi-View Image-to-Image Translation 通过多视图图像到图像转换的概率植物建模 | |
| 718.Progressive Attention Guided Recurrent Network for Salient Object Detection 渐进式注意力引导循环网络用于显着物体检测 | |
| 719.Progressively Complementarity-Aware Fusion Network for RGB-D Salient Object Detection 用于RGB-D显着目标检测的渐进式互补感知融合网络 | |
| 720.Pseudo Mask Augmented Object Detection 伪蒙版增强对象检测 | |
| 721.Pulling Actions out of Context: Explicit Separation for Effective Combination 使动作脱离上下文：有效组合的显式分离 | |
| 722.PU-Net: Point Cloud Upsampling Network PU-Net：点云上采样网络 | |
| 723.PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume PWC-Net：使用金字塔，翘曲和成本量的光流CNN | |
| 724.Pyramid Stereo Matching Network 金字塔立体匹配网络 | |
| 725.Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference 神经网络的量化和训练，以便进行有效的仅整数运算 | |
| 726.Quantization of Fully Convolutional Networks for Accurate Biomedical Image Segmentation 完全卷积网络的量化，用于精确的生物医学图像分割 | |
| 727.Radially-Distorted Conjugate Translations 径向变形的共轭翻译 | |
| 728.RayNet: Learning Volumetric 3D Reconstruction With Ray Potentials RayNet：使用射线势学习体积3D重建 | |
| 729.Real-Time Monocular Depth Estimation Using Synthetic Data With Domain Adaptation via Image Style Transfer 通过图像样式转移使用具有域自适应的合成数据进行实时单眼深度估计 | |
| 730.Real-Time Rotation-Invariant Face Detection With Progressive Calibration Networks 渐进式校准网络的实时旋转不变人脸检测 | |
| 731.Real-Time Seamless Single Shot 6D Object Pose Prediction 实时无缝单发6D对象姿态预测 | |
| 732.Real-World Anomaly Detection in Surveillance Videos 监控视频中的真实世界异常检测 | |
| 733.Real-World Repetition Estimation by Div, Grad and Curl 通过Div，Grad和Curl进行真实世界的重复估计 | |
| 734.Recognize Actions by Disentangling Components of Dynamics 通过解开动力学的成分来识别动作 | |
| 735.Recognizing Human Actions as the Evolution of Pose Estimation Maps 将人类行为识别为姿势估计图的演变 | |
| 736.Reconstructing Thin Structures of Manifold Surfaces by Integrating Spatial Curves 通过积分空间曲线重建歧管表面的薄结构 | |
| 737.Reconstruction Network for Video Captioning 视频字幕重建网络 | |
| 738.Recovering Realistic Texture in Image Super-Resolution by Deep Spatial Feature Transform 通过深度空间特征变换在图像超分辨率中恢复逼真的纹理 | |
| 739.Recurrent Pixel Embedding for Instance Grouping 用于实例分组的递归像素嵌入 | |
| 740.Recurrent Residual Module for Fast Inference in Videos 递归残差模块，可快速推断视频 | |
| 741.Recurrent Saliency Transformation Network: Incorporating Multi-Stage Visual Cues for Small Organ Segmentation 循环显着性转换网络：结合多阶段视觉提示进行小器官分割 | |
| 742.Recurrent Scene Parsing With Perspective Understanding in the Loop 循环场景解析与透视理解 | |
| 743.Recurrent Slice Networks for 3D Segmentation of Point Clouds 用于点云3D分割的递归切片网络 | |
| 744.Referring Image Segmentation via Recurrent Refinement Networks 通过递归细化网络引用图像分割 | |
| 745.Referring Relationships 推荐关系 | |
| 746.Reflection Removal for Large-Scale 3D Point Clouds 大型3D点云的反射消除 | |
| 747.Regularizing Deep Networks by Modeling and Predicting Label Structure 通过建模和预测标签结构来规范化深层网络 | |
| 748.Regularizing RNNs for Caption Generation by Reconstructing the Past With the Present 通过重建过去与现在来规范RNN以生成字幕 | |
| 749.Reinforcement Cutting-Agent Learning for Video Object Segmentation 用于视频对象分割的增强切割代理学习 | |
| 750.Relation Networks for Object Detection 用于对象检测的关系网络 |
| 论文 | 概要 |
|---|---|
| 751.Representing and Learning High Dimensional Data With the Optimal Transport Map From a Probabilistic Viewpoint 从概率角度用最佳传输图表示和学习高维数据 | |
| 752.Repulsion Loss: Detecting Pedestrians in a Crowd 排斥力损失：检测人群中的行人 | |
| 753.Residual Dense Network for Image Super-Resolution 残留密集网络可实现图像超分辨率 | |
| 754.Residual Parameter Transfer for Deep Domain Adaptation 深度域适应的残差参数传递 | |
| 755.Resource Aware Person Re-Identification Across Multiple Resolutions 跨多种解决方案的资源感知人员重新识别 | |
| 756.Rethinking Feature Distribution for Loss Functions in Image Classification 对图像分类中损失函数的特征分布的重新思考 | |
| 757.Rethinking the Faster R-CNN Architecture for Temporal Action Localization 重新思考用于时间动作本地化的更快的R-CNN架构 | |
| 758.Revisiting Deep Intrinsic Image Decompositions 重新审视深度内在图像分解 | |
| 759.Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi-Supervised Semantic Segmentation 重访扩张式卷积：一种用于弱监督和半监督语义分割的简单方法 | |
| 760.Revisiting Knowledge Transfer for Training Object Class Detectors 复习训练对象类别检测器的知识转移 | |
| 761.Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking 重温牛津和巴黎：大型图像检索基准 | |
| 762.Revisiting Salient Object Detection: Simultaneous Detection, Ranking, and Subitizing of Multiple Salient Objects 回顾显着对象检测：多个显着对象的同时检测，排序和细分 | |
| 763.Revisiting Video Saliency: A Large-Scale Benchmark and a New Model 回顾视频显着性：大规模基准和新模型 | |
| 764.Reward Learning From Narrated Demonstrations 叙述式学习中的奖励学习 | |
| 765.Re-Weighted Adversarial Adaptation Network for Unsupervised Domain Adaptation 无权域适应的加权加权对抗适应网络 | |
| 766.R-FCN-3000 at 30fps: Decoupling Detection and Classification R-FCN-3000的30fps：解耦检测和分类 | |
| 767.Ring Loss: Convex Feature Normalization for Face Recognition 环损：用于面部识别的凸特征归一化 | |
| 768.ROAD: Reality Oriented Adaptation for Semantic Segmentation of Urban Scenes ROAD：针对城市场景的语义分割的面向现实的适应 | |
| 769.RoadTracer: Automatic Extraction of Road Networks From Aerial Images RoadTracer：从航拍图像中自动提取路网 | |
| 770.Robust Classification With Convolutional Prototype Learning 卷积原型学习的鲁棒分类 | |
| 771.Robust Depth Estimation From Auto Bracketed Images 通过自动包围曝光图像进行稳健的深度估计 | |
| 772.Robust Facial Landmark Detection via a Fully-Convolutional Local-Global Context Network 通过全卷积局部全局上下文网络进行鲁棒的面部地标检测 | |
| 773.Robust Hough Transform Based 3D Reconstruction From Circular Light Fields 基于鲁棒霍夫变换的圆形光场3D重构 | |
| 774.Robust Physical-World Attacks on Deep Learning Visual Classification 深度学习视觉分类的强大物理世界攻击 | |
| 775.Robust Video Content Alignment and Compensation for Rain Removal in a CNN Framework CNN框架中针对雨水去除的强大视频内容对齐和补偿 | |
| 776.Rolling Shutter and Radial Distortion Are Features for High Frame Rate Multi-Camera Tracking 滚动快门和径向失真是高帧率多摄像机跟踪的功能 | |
| 777.Rotation Averaging and Strong Duality 旋转平均和强对偶 | |
| 778.RotationNet: Joint Object Categorization and Pose Estimation Using Multiviews From Unsupervised Viewpoints RotationNet：使用来自无监督观点的多视图进行联合对象分类和姿势估计 | |
| 779.Rotation-Sensitive Regression for Oriented Scene Text Detection 面向场景文本检测的旋转敏感回归 | |
| 780.Salience Guided Depth Calibration for Perceptually Optimized Compressive Light Field 3D Display 针对感知优化的压缩光场3D显示的显着性深度深度校准 | |
| 781.Salient Object Detection Driven by Fixation Prediction 固定预测驱动的显着物体检测 | |
| 782.SBNet: Sparse Blocks Network for Fast Inference SBNet：稀疏块网络以进行快速推理 | |
| 783.Scalable and Effective Deep CCA via Soft Decorrelation 通过软解相关可扩展且有效的深度CCA | |
| 784.Scalable Dense Non-Rigid Structure-From-Motion: A Grassmannian Perspective 运动可伸缩的密集非刚性结构：格拉斯曼观点 | |
| 785.Scale-Recurrent Network for Deep Image Deblurring 用于深度图像去模糊的缩放递归网络 | |
| 786.Scale-Transferrable Object Detection 可缩放的目标检测 | |
| 787.ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans ScanComplete：3D扫描的大规模场景完成和语义分割 | |
| 788.SeedNet: Automatic Seed Generation With Deep Reinforcement Learning for Robust Interactive Segmentation SeedNet：具有深度强化学习功能的自动种子生成，可实现可靠的交互式细分 | |
| 789.Seeing Small Faces From Robust Anchor’s Perspective 从稳固的锚点角度看小脸 | |
| 790.Seeing Temporal Modulation of Lights From Standard Cameras 从标准相机看到光的时间调制 | |
| 791.Seeing Voices and Hearing Faces: Cross-Modal Biometric Matching 看到声音和听觉的面孔：跨模态生物特征匹配 | |
| 792.SeGAN: Segmenting and Generating the Invisible SeGAN：分割和生成不可见 | |
| 793.Self-Calibrating Polarising Radiometric Calibration 自校准偏振辐射校准 | |
| 794.Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval 自我监督的对抗式哈希网络，用于跨模态检索 | |
| 795.Self-Supervised Feature Learning by Learning to Spot Artifacts 通过学习发现伪像进行自我监督的特征学习 | |
| 796.Self-Supervised Learning of Geometrically Stable Features Through Probabilistic Introspection 通过概率自省对几何稳定特征进行自我监督学习 | |
| 797.Self-Supervised Multi-Level Face Model Learning for Monocular Reconstruction at Over 250 Hz 用于250 Hz以上单眼重建的自监督多级面部模型学习 | |
| 798.Semantic Video Segmentation by Gated Recurrent Flow Propagation 门控循环流传播的语义视频分割 | |
| 799.Semantic Visual Localization 语义视觉本地化 | |
| 800.Semi-Parametric Image Synthesis 半参数图像合成 |
| 论文 | 概要 |
|---|---|
| 801.SemStyle: Learning to Generate Stylised Image Captions Using Unaligned Text SemStyle：学习使用未对齐的文本生成样式化的图像标题 | |
| 802.Separating Self-Expression and Visual Content in Hashtag Supervision 在标签监督中分离自我表达和视觉内容 | |
| 803.Separating Style and Content for Generalized Style Transfer 分隔样式和内容以进行广义样式转移 | |
| 804.SfSNet: Learning Shape, Reflectance and Illuminance of Faces `in the Wild’ SfSNet：学习“野外”面孔的形状，反射率和照度 | |
| 805.SGAN: An Alternative Training of Generative Adversarial Networks SGAN：生成对抗网络的替代培训 | |
| 806.SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation SGPN：3D点云实例细分的相似性组建议网络 | |
| 807.Shape From Shading Through Shape Evolution 从阴影到形状进化 | |
| 808.Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions 移位：零卷积，零参数替代空间卷积 | |
| 809.Show Me a Story: Towards Coherent Neural Story Illustration 告诉我一个故事：迈向连贯的神经故事插图 | |
| 810.ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices ShuffleNet：用于移动设备的极其高效的卷积神经网络 | |
| 811.Sim2Real Viewpoint Invariant Visual Servoing by Recurrent Control 通过递归控制实现Sim2Real Viewpoint不变视觉伺服 | |
| 812.Single Image Dehazing via Conditional Generative Adversarial Network 通过条件生成对抗网络进行单图像去雾 | |
| 813.Single-Image Depth Estimation Based on Fourier Domain Analysis 基于傅立叶域分析的单图像深度估计 | |
| 814.Single Image Reflection Separation With Perceptual Losses 具有感知损失的单图像反射分离 | |
| 815.Single-Shot Object Detection With Enriched Semantics 具有丰富语义的单发目标检测 | |
| 816.Single-Shot Refinement Neural Network for Object Detection 用于目标检测的单发细化神经网络 | |
| 817.Single View Stereo Matching 单视图立体声匹配 | |
| 818.SINT++: Robust Visual Tracking via Adversarial Positive Instance Generation SINT ++：通过对抗性积极实例生成进行可靠的视觉跟踪 | |
| 819.Sketch-a-Classifier: Sketch-Based Photo Classifier Generation 草图分类器：基于草图的照片分类器生成 | |
| 820.SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval SketchMate：数以百万计的人类草图检索的深度哈希 | |
| 821.SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis SketchyGAN：向图像合成中逼真的素描 | |
| 822.Sliced Wasserstein Distance for Learning Gaussian Mixture Models 切片Wasserstein距离用于学习高斯混合模型 | |
| 823.Smooth Neighbors on Teacher Graphs for Semi-Supervised Learning 教师图上的平滑邻居用于半监督学习 | |
| 824.SobolevFusion: 3D Reconstruction of Scenes Undergoing Free Non-Rigid Motion SobolevFusion：进行自由非刚性运动的场景的3D重建 | |
| 825.Soccer on Your Tabletop 桌上足球 | |
| 826.Social GAN: Socially Acceptable Trajectories With Generative Adversarial Networks 社交GAN：具有生成对抗网络的社交可接受轨迹 | |
| 827.Solving the Perspective-2-Point Problem for Flying-Camera Photo Composition 解决飞行相机照片构图的透视2点问题 | |
| 828.SO-Net: Self-Organizing Network for Point Cloud Analysis SO-Net：用于点云分析的自组织网络 | |
| 829.SoS-RSC: A Sum-of-Squares Polynomial Approach to Robustifying Subspace Clustering Algorithms SoS-RSC：一种平方和多项式方法，用于鲁棒子空间聚类算法 | |
| 830.Sparse Photometric 3D Face Reconstruction Guided by Morphable Models 可变形模型指导的稀疏光度3D人脸重建 | |
| 831.Sparse, Smart Contours to Represent and Edit Images 稀疏的智能轮廓来表示和编辑图像 | |
| 832.Spatially-Adaptive Filter Units for Deep Neural Networks 用于深度神经网络的空间自适应滤波器单元 | |
| 833.SPLATNet: Sparse Lattice Networks for Point Cloud Processing SPLATNet：用于点云处理的稀疏格子网络 | |
| 834.SplineCNN: Fast Geometric Deep Learning With Continuous B-Spline Kernels SplineCNN：具有连续B样条曲线核的快速几何深度学习 | |
| 835.Spline Error Weighting for Robust Visual-Inertial Fusion 样条误差加权，实现稳健的视觉惯性融合 | |
| 836.Squeeze-and-Excitation Networks 挤压和激励网络 | |
| 837.SSNet: Scale Selection Network for Online 3D Action Prediction SSNet：在线3D动作预测的量表选择网络 | |
| 838.Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal 联合学习阴影检测和阴影去除的堆叠条件生成对抗网络 | |
| 839.Stacked Latent Attention for Multimodal Reasoning 多模态推理的堆叠潜在注意力 | |
| 840.StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation StarGAN：用于多域图像到图像翻译的统一生成对抗网络 | |
| 841.Statistical Tomography of Microscopic Life 微观生命的统计断层扫描 | |
| 842.Stereoscopic Neural Style Transfer 立体神经风格转换 | |
| 843.ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing ST-GAN：用于图像合成的空间变压器生成对抗网络 | |
| 844.Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks 卷积网络中用于成本可调推断和改进正则化的随机下采样 | |
| 845.Stochastic Variational Inference With Gradient Linearization 梯度线性化的随机变分推断 | |
| 846.Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation 结构化注意力导向的卷积神经场用于单眼深度估计 | |
| 847.Structured Set Matching Networks for One-Shot Part Labeling 一站式零件贴标的结构化集合匹配网络 | |
| 848.Structured Uncertainty Prediction Networks 结构化不确定性预测网络 | |
| 849.Structure From Recurrent Motion: From Rigidity to Recurrency 循环运动的结构：从刚度到递归 | |
| 850.Structure Inference Net: Object Detection Using Scene-Level Context and Instance-Level Relationships 结构推断网：使用场景级上下文和实例级关系的对象检测 |
| 论文 | 概要 |
|---|---|
| 851.Structure Preserving Video Prediction 保留结构的视频预测 | |
| 852.Style Aggregated Network for Facial Landmark Detection 用于面部地标检测的样式聚合网络 | |
| 853.Super-FAN: Integrated Facial Landmark Localization and Super-Resolution of Real-World Low Resolution Faces in Arbitrary Poses With GANs Super-FAN：具有GAN的任意姿势中的集成面部地标定位和真实世界低分辨率面孔的超分辨率 | |
| 854.Super-Resolving Very Low-Resolution Face Images With Supplementary Attributes 具有补充属性的超分辨率超低分辨率人脸图像 | |
| 855.Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation Super SloMo：用于视频插值的多个中间帧的高质量估计 | |
| 856.Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors 注册监督：一种无监督的方法来提高面部地标检测器的精度 | |
| 857.Surface Networks 地面网络 | |
| 858.SurfConv: Bridging 3D and 2D Convolution for RGBD Images SurfConv：桥接RGBD图像的3D和2D卷积 | |
| 859.Synthesizing Images of Humans in Unseen Poses 在看不见的姿势中合成人的形象 | |
| 860.SYQ: Learning Symmetric Quantization for Efficient Deep Neural Networks SYQ：为高效的深度神经网络学习对称量化 | |
| 861.Tagging Like Humans: Diverse and Distinct Image Annotation 像人类一样标记：多样化且独特的图像注释 | |
| 862.Tags2Parts: Discovering Semantic Regions From Shape Tags 标签2部分：从形状标签中发现语义区域 | |
| 863.Tangent Convolutions for Dense Prediction in 3D 切线卷积用于3D密集预测 | |
| 864.Taskonomy: Disentangling Task Transfer Learning Taskonomy：解开任务转移学习 | |
| 865.Teaching Categories to Human Learners With Visual Explanations 用视觉解释向人类学习者教授类别 | |
| 866.Tell Me Where to Look: Guided Attention Inference Network 告诉我在哪里看：引导注意推理网络 | |
| 867.Temporal Deformable Residual Networks for Action Segmentation in Videos 视频中的时间分段的时间可变形残差网络 | |
| 868.Temporal Hallucinating for Action Recognition With Few Still Images 时间幻觉的动作识别很少有静止图像 | |
| 869.Tensorize, Factorize and Regularize: Robust Visual Relationship Learning 张量化，分解和正则化：稳健的视觉关系学习 | |
| 870.Textbook Question Answering Under Instructor Guidance With Memory Networks 记忆网络下教师指导下的教科书问答 | |
| 871.TextureGAN: Controlling Deep Image Synthesis With Texture Patches TextureGAN：使用纹理补丁控制深度图像合成 | |
| 872.Texture Mapping for 3D Reconstruction With RGB-D Sensor 使用RGB-D传感器进行3D重建的纹理映射 | |
| 873.The Best of Both Worlds: Combining CNNs and Geometric Constraints for Hierarchical Motion Segmentation 两全其美：结合CNN和几何约束进行分层运动分割 | |
| 874.The INaturalist Species Classification and Detection Dataset 非自然物种分类和检测数据集 | |
| 875.The LovaSz-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks LovaSz-Softmax损失：神经网络交叉口联合测量的优化的可替代替代方法 | |
| 876.The Perception-Distortion Tradeoff 感知失真权衡 | |
| 877.The Power of Ensembles for Active Learning in Image Classification 集成在图像分类中主动学习的力量 | |
| 878.The Unreasonable Effectiveness of Deep Features as a Perceptual Metric 深度特征作为感知指标的不合理有效性 | |
| 879.Thoracic Disease Identification and Localization With Limited Supervision 有限监督下的胸腔疾病鉴定和定位 | |
| 880.Through-Wall Human Pose Estimation Using Radio Signals 使用无线电信号的全程人体姿态估计 | |
| 881.TieNet: Text-Image Embedding Network for Common Thorax Disease Classification and Reporting in Chest X-Rays TieNet：普通胸部疾病分类和胸部X光报告的文本图像嵌入网络 | |
| 882.Time-Resolved Light Transport Decomposition for Thermal Photometric Stereo 热光度立体的时间分辨光传输分解 | |
| 883.Tips and Tricks for Visual Question Answering: Learnings From the 2017 Challenge 视觉问题解答的提示和技巧：2017年挑战的经验教训 | |
| 884.TOM-Net: Learning Transparent Object Matting From a Single Image TOM-Net：从单个图像学习透明对象遮罩 | |
| 885.Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies 总捕获：用于跟踪面部，手部和身体的3D变形模型 | |
| 886.Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning 对驾驶场景的理解：学习驾驶员行为和因果推理的数据集 | |
| 887.Towards a Mathematical Understanding of the Difficulty in Learning With Feedforward Neural Networks 对前馈神经网络学习困难的数学理解 | |
| 888.Towards Dense Object Tracking in a 2D Honeybee Hive 在2D蜜蜂蜂巢中实现密集对象跟踪 | |
| 889.Towards Effective Low-Bitwidth Convolutional Neural Networks 迈向有效的低位宽卷积神经网络 | |
| 890.Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization 通过迭代矩阵平方根归一化来更快地训练全局协方差合并网络 | |
| 891.Towards High Performance Video Object Detection 迈向高性能视频目标检测 | |
| 892.Towards Human-Machine Cooperation: Self-Supervised Sample Mining for Object Detection 走向人机合作：用于对象检测的自监督样本挖掘 | |
| 893.Towards Open-Set Identity Preserving Face Synthesis 迈向开放式身份保留人脸综合 | |
| 894.Towards Pose Invariant Face Recognition in the Wild 走向野外姿势不变的人脸识别 | |
| 895.Towards Universal Representation for Unseen Action Recognition 走向通用表示以实现看不见的动作识别 | |
| 896.Tracking Multiple Objects Outside the Line of Sight Using Speckle Imaging 使用散斑成像跟踪视线外的多个物体 | |
| 897.Transductive Unbiased Embedding for Zero-Shot Learning 零射学习的传导无偏嵌入 | |
| 898.Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification 可转移的联合属性-身份深度学习，用于无监督人员重新识别 | |
| 899.Translating and Segmenting Multimodal Medical Volumes With Cycle- and Shape-Consistency Generative Adversarial Network 使用周期和形状一致性生成对抗网络对多峰医疗量进行翻译和分段 | |
| 900.Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning 设计上的透明度：弥合视觉推理中性能和可解释性之间的差距 |
| 论文 | 概要 |
|---|---|
| 901.Trapping Light for Time of Flight 飞行时间的陷阱灯 | |
| 902.Triplet-Center Loss for Multi-View 3D Object Retrieval 多视图3D对象检索的三重态中心损失 | |
| 903.Trust Your Model: Light Field Depth Estimation With Inline Occlusion Handling 信任您的模型：内联遮挡处理的光场深度估计 | |
| 904.Two Can Play This Game: Visual Dialog With Discriminative Question Generation and Answering 两个人可以玩这个游戏：具有判别性问题生成和回答的可视对话框 | |
| 905.Two-Step Quantization for Low-Bit Neural Networks 低位神经网络的两步量化 | |
| 906.Two-Stream Convolutional Networks for Dynamic Texture Synthesis 用于动态纹理合成的两流卷积网络 | |
| 907.Uncalibrated Photometric Stereo Under Natural Illumination 自然照明下未经校准的测光立体 | |
| 908.Unifying Identification and Context Learning for Person Recognition 统一身份识别和上下文学习以实现人的识别 | |
| 909.Universal Denoising Networks : A Novel CNN Architecture for Image Denoising 通用降噪网络：一种用于图像降噪的新型CNN架构 | |
| 910.Unsupervised Correlation Analysis 无监督相关分析 | |
| 911.Unsupervised Cross-Dataset Person Re-Identification by Transfer Learning of Spatial-Temporal Patterns 通过时空模式的转移学习对无监督的跨数据集人员进行重新识别 | |
| 912.Unsupervised Deep Generative Adversarial Hashing Network 无监督的深度生成对抗式哈希网络 | |
| 913.Unsupervised Discovery of Object Landmarks as Structural Representations 无监督地发现对象地标作为结构表示形式 | |
| 914.Unsupervised Domain Adaptation With Similarity Learning 具有相似性学习的无监督域自适应 | |
| 915.Unsupervised Feature Learning via Non-Parametric Instance Discrimination 通过非参数实例区分进行无监督特征学习 | |
| 916.Unsupervised Learning and Segmentation of Complex Activities From Video 视频的无监督学习和复杂活动细分 | |
| 917.Unsupervised Learning of Depth and Ego-Motion From Monocular Video Using 3D Geometric Constraints 使用3D几何约束从单眼视频进行无监督的深度和自我运动学习 | |
| 918.Unsupervised Learning of Monocular Depth Estimation and Visual Odometry With Deep Feature Reconstruction 具有深度特征重构的单眼深度估计和视觉测程的无监督学习 | |
| 919.Unsupervised Person Image Synthesis in Arbitrary Poses 任意姿势下的无人监督图像合成 | |
| 920.Unsupervised Sparse Dirichlet-Net for Hyperspectral Image Super-Resolution 无监督稀疏Dirichlet-Net用于高光谱图像超分辨率 | |
| 921.Unsupervised Textual Grounding: Linking Words to Image Concepts 无监督的文本基础：将单词链接到图像概念 | |
| 922.Unsupervised Training for 3D Morphable Model Regression 3D变形模型回归的无监督训练 | |
| 923.UV-GAN: Adversarial Facial UV Map Completion for Pose-Invariant Face Recognition UV-GAN：对抗性面部UV贴图完成，用于姿势不变的面部识别 | |
| 924.V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation From a Single Depth Map V2V-PoseNet：用于从单个深度图进行精确3D手和人姿估计的体素到体素预测网络 | |
| 925.Variational Autoencoders for Deforming 3D Mesh Models 变形3D网格模型的变体自动编码器 | |
| 926.Very Large-Scale Global SfM by Distributed Motion Averaging 分布式运动平均的超大规模全球SfM | |
| 927.Video Based Reconstruction of 3D People Models 基于视频的3D人模型重构 | |
| 928.Video Captioning via Hierarchical Reinforcement Learning 通过分层强化学习进行视频字幕 | |
| 929.Video Person Re-Identification With Competitive Snippet-Similarity Aggregation and Co-Attentive Snippet Embedding 具有竞争性摘要相似性聚合和共同关注性摘要嵌入的视频人重新识别 | |
| 930.Video Rain Streak Removal by Multiscale Convolutional Sparse Coding 多尺度卷积稀疏编码去除视频雨纹 | |
| 931.Video Representation Learning Using Discriminative Pooling 使用区分池的视频表示学习 | |
| 932.View Extrapolation of Human Body From a Single Image 从单个图像查看人体外推 | |
| 933.Viewpoint-Aware Attentive Multi-View Inference for Vehicle Re-Identification 用于车辆重新识别的具有视点意识的多视图推理 | |
| 934.Viewpoint-Aware Video Summarization 视点感知视频摘要 | |
| 935.VirtualHome: Simulating Household Activities via Programs VirtualHome：通过程序模拟家庭活动 | |
| 936.Vision-and-Language Navigation: Interpreting Visually-Grounded Navigation Instructions in Real Environments 视觉和语言导航：解释真实环境中的视觉地面导航说明 | |
| 937.Visual Feature Attribution Using Wasserstein GANs 使用Wasserstein GAN的视觉特征归因 | |
| 938.Visual Grounding via Accumulated Attention 通过累积注意力进行视觉接地 | |
| 939.Visual Question Answering With Memory-Augmented Networks 内存增强网络的视觉问题解答 | |
| 940.Visual Question Generation as Dual Task of Visual Question Answering 视觉问题生成是视觉问题回答的双重任务 | |
| 941.Visual Question Reasoning on General Dependency Tree 一般依赖树上的视觉问题推理 | |
| 942.Visual to Sound: Generating Natural Sound for Videos in the Wild 视觉到声音：为野外视频生成自然声音 | |
| 943.VITAL: VIsual Tracking via Adversarial Learning VITAL：通过对抗性学习进行视觉跟踪 | |
| 944.VITON: An Image-Based Virtual Try-On Network VITON：基于映像的虚拟试穿网络 | |
| 945.VizWiz Grand Challenge: Answering Visual Questions From Blind People VizWiz大挑战：回答盲人的视觉问题 | |
| 946.VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection VoxelNet：基于点云的3D对象检测的端到端学习 | |
| 947.W2F: A Weakly-Supervised to Fully-Supervised Framework for Object Detection W2F：弱监督到完全监督的对象检测框架 | |
| 948.Wasserstein Introspective Neural Networks Wasserstein自省神经网络 | |
| 949.Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer 通过姿势指导的知识转移进行弱而半监督的人体部位解析 | |
| 950.Weakly Supervised Action Localization by Sparse Temporal Pooling Network 稀疏时间池网络对行为的弱监督 |
| 论文 | 概要 |
|---|---|
| 951.Weakly-Supervised Action Segmentation With Iterative Soft Boundary Assignment 具有迭代软边界分配的弱监督动作细分 | |
| 952.Weakly Supervised Coupled Networks for Visual Sentiment Analysis 弱监督耦合网络，用于视觉情感分析 | |
| 953.Weakly-Supervised Deep Convolutional Neural Network Learning for Facial Action Unit Intensity Estimation 弱监督深度卷积神经网络学习，用于面部动作单元强度估计 | |
| 954.Weakly Supervised Facial Action Unit Recognition Through Adversarial Training 通过对抗训练对面部动作单元识别进行监督不足 | |
| 955.Weakly Supervised Instance Segmentation Using Class Peak Response 使用类峰值响应的弱监督实例分割 | |
| 956.Weakly Supervised Learning of Single-Cell Feature Embeddings 单细胞特征嵌入的弱监督学习 | |
| 957.Weakly Supervised Phrase Localization With Multi-Scale Anchored Transformer Network 多尺度锚定变压器网络的弱监督短语定位 | |
| 958.Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features 通过迭代挖掘常见对象特征的弱监督语义分割 | |
| 959.Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region Growing 具有深度种子区域增长的弱监督语义分割网络 | |
| 960.Webly Supervised Learning Meets Zero-Shot Learning: A Hybrid Approach for Fine-Grained Classification 网上监督学习与零射击学习：精细分类的混合方法 | |
| 961.What Do Deep Networks Like to See? 深度网络喜欢看什么？ | |
| 962.What Have We Learned From Deep Representations for Action Recognition? 我们从用于动作识别的深度表示中学到了什么？ | |
| 963.What Makes a Video a Video: Analyzing Temporal Information in Video Understanding Models and Datasets 是什么使视频成为视频：分析视频中的时间信息了解模型和数据集 | |
| 964.When Will You Do What? - Anticipating Temporal Occurrences of Activities 您什么时候会做什么？ -预期活动的临时发生 | |
| 965.Where and Why Are They Looking? Jointly Inferring Human Attention and Intentions in Complex Tasks 他们在哪里看，为什么看？共同推断人类的注意力和复杂任务中的意图 | |
| 966.Who Let the Dogs Out? Modeling Dog Behavior From Visual Data 谁让狗出去了？根据视觉数据模拟狗的行为 | |
| 967.Who’s Better? Who’s Best? Pairwise Deep Ranking for Skill Determination 谁更好？谁最好成对确定技能的深度排名 | |
| 968.Wide Compression: Tensor Ring Nets 宽压缩：张量环网 | |
| 969.WILDTRACK: A Multi-Camera HD Dataset for Dense Unscripted Pedestrian Detection WILDTRACK：用于密集无脚本行人检测的多摄像机高清数据集 | |
| 970.Wing Loss for Robust Facial Landmark Localisation With Convolutional Neural Networks 用卷积神经网络进行稳健的人脸地标定位的机翼损失 | |
| 971.Wrapped Gaussian Process Regression on Riemannian Manifolds 黎曼流形上的包裹高斯过程回归 | |
| 972.xUnit: Learning a Spatial Activation Function for Efficient Image Restoration xUnit：学习空间激活功能以进行有效的图像恢复 | |
| 973.Zero-Shot Kernel Learning 零射内核学习 | |
| 974.Zero-Shot Recognition via Semantic Embeddings and Knowledge Graphs 通过语义嵌入和知识图进行零散识别 | |
| 975.Zero-Shot Sketch-Image Hashing 零射素描图像散列 | |
| 976.“Zero-Shot” Super-Resolution Using Deep Internal Learning 使用深度内部学习的“零射击”超分辨率 | |
| 977.Zero-Shot Visual Recognition Using Semantics-Preserving Adversarial Embedding Networks 保留语义对抗性嵌入网络的零射视觉识别 | |
| 978.Zigzag Learning for Weakly Supervised Object Detection 锯齿形学习用于弱监督对象检测 | |
| 979.Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains 缩放和学习：将深度立体声匹配推广到新颖领域 |
最后
以上就是细腻刺猬最近收集整理的关于（十：2020.08.28）CVPR 2018 追踪之论文纲要（译）讲在前面论文目录的全部内容，更多相关（十：2020.08.28）CVPR内容请搜索靠谱客的其他文章。
本图文内容来源于网友提供，作为学习参考使用，或来自网络收集整理，版权属于原作者所有。
发表评论 取消回复