我是靠谱客的博主 矮小大门,最近开发中收集的这篇文章主要介绍CVPR 2020 全部论文 分类汇总和打包下载总目录图像处理图像分类目标检测和分割视觉目标跟踪视频内容分析(理解)人体关键点检测和姿态估计模型轻量化和加速神经网络架构设计和搜索NAS生成对抗GAN三维点云&3D重建光学字符识别OCR迁移学习弱监督 & 无监督学习人脸识别图神经网络GNN视觉 & 语言 混合任务研究其他问题研究论文打包下载地址,觉得挺不错的,现在分享给大家,希望可以做个参考。

概述

CVPR 2020 共收录 1470篇文章,根据当前的公布情况,人工智能学社整理了以下约100篇,分享给读者。

代码开源情况:详见每篇注释,当前共15篇开源。(持续更新中,可关注了解)。

算法主要领域:图像与视频处理,图像分类&检测&分割、视觉目标跟踪、视频内容分析、人体姿态估计、模型加速、网络架构搜索(NAS)、生成对抗(GAN)、光学字符识别(OCR)、人脸识别、三维重建等方向。 目录如下:

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总目录

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图像处理

  1. Deep Image Harmonization via Domain Verification
    论文:https://arxiv.org/abs/1911.13239
    代码:https://github.com/bcmi/Image_Harmonization_Datasets

  2. Learning to Shade Hand-drawn Sketches
    论文:https://arxiv.org/abs/2002.11812

  3. Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data
    论文:https://arxiv.org/abs/2002.11297

  4. Single Image Reflection Removal through Cascaded Refinement
    论文:https://arxiv.org/abs/1911.06634

  5. RoutedFusion: Learning Real-time Depth Map Fusion
    论文:https://arxiv.org/pdf/2001.04388.pdf

图像分类

  1. Towards Robust Image Classification Using Sequential Attention Models
    论文:https://arxiv.org/abs/1912.02184

  2. Self-training with Noisy Student improves ImageNet classification
    论文:https://arxiv.org/abs/1911.04252

  3. Image Matching across Wide Baselines: From Paper to Practice
    论文:https://arxiv.org/abs/2003.01587

  4. Improved Few-Shot Visual Classification
    论文:https://arxiv.org/pdf/1912.03432.pdf

  5. A General and Adaptive Robust Loss Function
    论文:https://arxiv.org/abs/1701.03077

  6. Making Better Mistakes: Leveraging Class Hierarchies with Deep Networks
    论文:https://arxiv.org/abs/1912.09393

目标检测和分割

  1. Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector
    论文:https://arxiv.org/abs/1908.01998

  2. Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection
    论文:https://arxiv.org/abs/1912.02424
    代码:https://github.com/sfzhang15/ATSS

  3. Semi-Supervised Semantic Image Segmentation with Self-correcting Networks
    论文:https://arxiv.org/abs/1811.07073

  4. Deep Snake for Real-Time Instance Segmentation
    论文:https://arxiv.org/abs/2001.01629

  5. SketchGCN: Semantic Sketch Segmentation with Graph Convolutional Networks
    论文:https://arxiv.org/abs/2003.00678

  6. xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation
    论文:https://arxiv.org/abs/1911.12676

  7. CenterMask : Real-Time Anchor-Free Instance Segmentation
    论文:https://arxiv.org/abs/1911.06667
    代码:https://github.com/youngwanLEE/CenterMask

  8. PolarMask: Single Shot Instance Segmentation with Polar Representation
    论文:https://arxiv.org/abs/1909.13226
    代码:https://github.com/xieenze/PolarMask

  9. BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation
    论文:https://arxiv.org/abs/2001.00309

视觉目标跟踪

  1. ROAM: Recurrently Optimizing Tracking Model
    论文:https://arxiv.org/abs/1907.12006

视频内容分析(理解)

  1. Hierarchical Conditional Relation Networks for Video Question Answering
    论文:https://arxiv.org/abs/2002.10698

  2. Rethinking Zero-shot Video Classification: End-to-end Training for Realistic Applications
    论文:https://arxiv.org/abs/2003.01455
    代码:https://github.com/bbrattoli/ZeroShotVideoClassification

  3. Action Modifiers:Learning from Adverbs in Instructional Video
    论文:https://arxiv.org/abs/1912.06617

  4. Fine-grained Video-Text Retrieval with Hierarchical Graph Reasoning
    论文:https://arxiv.org/abs/2003.00392

  5. Blurry Video Frame Interpolation
    论文:https://arxiv.org/abs/2002.12259

  6. Object Relational Graph with Teacher-Recommended Learning for Video Captioning
    论文:https://arxiv.org/abs/2002.11566

  7. Say As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene Graphs
    论文:https://arxiv.org/abs/2003.00387

  8. Learning Representations by Predicting Bags of Visual Words
    论文:https://arxiv.org/abs/2002.12247

  9. Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution
    论文:https://arxiv.org/abs/2002.11616

人体关键点检测和姿态估计

  1. Distribution-Aware Coordinate Representation for Human Pose Estimation
    论文:https://arxiv.org/abs/1910.06278
    代码:https://github.com/ilovepose/DarkPose

  2. VIBE: Video Inference for Human Body Pose and Shape Estimation
    论文:https://arxiv.org/abs/1912.05656
    代码:https://github.com/mkocabas/VIBE

  3. The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose Estimation
    论文:https://arxiv.org/abs/1911.07524

  4. Optimal least-squares solution to the hand-eye calibration problem
    论文:https://arxiv.org/abs/2002.10838

  5. Distribution Aware Coordinate Representation for Human Pose Estimation
    论文:https://arxiv.org/abs/1910.06278

  6. D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry
    论文:https://arxiv.org/abs/2003.01060

  7. Multi-Modal Domain Adaptation for Fine-Grained Action Recognition
    论文:https://arxiv.org/abs/2001.09691

  8. PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimation
    论文:https://arxiv.org/abs/1911.04231

  9. 4D Association Graph for Realtime Multi-person Motion Capture Using Multiple Video Cameras
    论文:https://arxiv.org/abs/2002.12625

模型轻量化和加速

  1. GPU-Accelerated Mobile Multi-view Style Transfer
    论文:https://arxiv.org/abs/2003.00706

神经网络架构设计和搜索NAS

  1. GhostNet: More Features from Cheap Operations
    论文:https://arxiv.org/abs/1911.11907
    代码:https://github.com/iamhankai/ghostnet

  2. CARS: Contunuous Evolution for Efficient Neural Architecture Search
    论文:https://arxiv.org/pdf/1909.04977.pdf
    代码:https://github.com/huawei-noah/CARS

  3. Visual Commonsense R-CNN
    论文:https://arxiv.org/abs/2002.12204

  4. Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral
    论文:https://arxiv.org/abs/2003.01826

  5. AdderNet: Do We Really Need Multiplications in Deep Learning?
    论文:https://arxiv.org/pdf/1912.13200

  6. Filter Grafting for Deep Neural Networks
    论文:https://arxiv.org/pdf/2001.05868.pdf

生成对抗GAN

  1. Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models
    论文:https://arxiv.org/abs/1911.12287
    代码:https://github.com/giannisdaras/ylg

  2. MSG-GAN: Multi-Scale Gradient GAN for Stable Image Synthesis
    论文:https://arxiv.org/abs/1903.06048

  3. Robust Design of Deep Neural Networks against Adversarial Attacks based on Lyapunov Theory
    论文:https://arxiv.org/abs/1911.04636

三维点云&3D重建

  1. PointAugment: an Auto-Augmentation Framework for Point Cloud Classification
    论文:https://arxiv.org/abs/2002.10876
    代码:https://github.com/liruihui/PointAugment/

  2. PF-Net: Point Fractal Network for 3D Point Cloud Completion
    论文:https://arxiv.org/abs/2003.00410

  3. Learning multiview 3D point cloud registration
    论文:https://arxiv.org/abs/2001.05119

  4. Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image
    论文:https://arxiv.org/abs/2002.12212

  5. In Perfect Shape: Certifiably Optimal 3D Shape Reconstruction from 2D Landmarks
    论文:https://arxiv.org/pdf/1911.11924.pdf

  6. RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds
    论文:https://arxiv.org/abs/1911.11236

  7. C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds
    论文:https://arxiv.org/abs/1912.07009

  8. Representations, Metrics and Statistics For Shape Analysis of Elastic Graphs
    论文:https://arxiv.org/abs/2003.00287

  9. Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion
    论文:https://arxiv.org/abs/2003.01456

光学字符识别OCR

  1. ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network
    论文:https://arxiv.org/abs/2002.10200
    代码:https://github.com/Yuliang-Liu/bezier_curve_text_spotting,https://github.com/aim-uofa/adet

迁移学习

  1. Meta-Transfer Learning for Zero-Shot Super-Resolution
    论文:https://arxiv.org/abs/2002.12213

  2. Transferring Dense Pose to Proximal Animal Classes
    论文:https://arxiv.org/abs/2003.00080

弱监督 & 无监督学习

  1. Unsupervised Reinforcement Learning of Transferable Meta-Skills for Embodied Navigation
    论文:https://arxiv.org/abs/1911.07450

  2. Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction
    论文:https://arxiv.org/abs/2003.01460

  3. Rethinking the Route Towards Weakly Supervised Object Localization
    论文:https://arxiv.org/abs/2002.11359

  4. NestedVAE: Isolating Common Factors via Weak Supervision
    论文:https://arxiv.org/abs/2002.11576

人脸识别

  1. Towards Universal Representation Learning for Deep Face Recognition
    论文:https://arxiv.org/abs/2002.11841

  2. Suppressing Uncertainties for Large-Scale Facial Expression Recognition
    论文:https://arxiv.org/abs/2002.10392
    代码:https://github.com/kaiwang960112/Self-Cure-Network

  3. Face X-ray for More General Face Forgery Detection
    论文:https://arxiv.org/pdf/1912.13458.pdf

图神经网络GNN

  1. Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction
    论文:https://arxiv.org/abs/2002.11927

  2. Bundle Adjustment on a Graph Processor
    论文:https://arxiv.org/abs/2003.03134
    代码:https://github.com/joeaortiz/gbp

视觉 & 语言 混合任务研究

  1. Towards Learning a Generic Agent for Vision-and-Language Navigation via Pre-training
    论文:https://arxiv.org/abs/2002.10638
    代码:https://github.com/weituo12321/PREVALENT

  2. 12-in-1: Multi-Task Vision and Language Representation Learning
    论文:https://arxiv.org/abs/1912.02315

  3. Hierarchical Conditional Relation Networks for Video Question Answering
    论文:https://arxiv.org/abs/2002.10698

其他问题研究

  1. What it Thinks is Important is Important: Robustness Transfers through Input Gradients
    论文:https://arxiv.org/abs/1912.05699

  2. Holistically-Attracted Wireframe Parsing
    论文:https://arxiv.org/abs/2003.01663

  3. Attentive Context Normalization for Robust Permutation-Equivariant Learning
    论文:https://arxiv.org/abs/1907.02545

  4. ClusterFit: Improving Generalization of Visual Representations
    论文:https://arxiv.org/abs/1912.03330

  5. Learning in the Frequency Domain
    论文:https://arxiv.org/abs/2002.12416

  6. A Characteristic Function Approach to Deep Implicit Generative Modeling
    论文:https://arxiv.org/abs/1909.07425

  7. Auto-Encoding Twin-Bottleneck Hashing
    论文:https://arxiv.org/abs/2002.11930

论文打包下载地址

链接:https://pan.baidu.com/s/1lo3smbFWiBSNnut9JssYaQ
提取码:公众号内回复 cvpr2020

论文包中有彩蛋一枚~~~~

最后

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