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ECCV 2020 论文汇总

(注意力模型、事件相机、知识蒸馏、图像去雾去雨去噪、图像超分辨率、语义分割,等方向)

         [oral, spotlight]

[Post]

[Dehazing]

[Enhancement]

[Dinoising]

[Deraining]

[Event]

[Attention]

[Super-Resolution]

[Wavelet]

[Bayesian]

[Semantic Segmentation]

[Distillation]



[oral, spotlight]

  • AiR: Attention with Reasoning Capability
  • Invertible Image Rescaling
  • End-to-End Object Detection with Transformers
  • Rewriting a Deep Generative Model
  • Conditional Convolutions for Instance Segmentation
  • Content-Aware Unsupervised Deep Homography Estimation
  • Gradient Centralization: A New Optimization Technique for Deep Neural Networks
  • Learning Stereo from Single Images
  • Diffraction Line Imaging
  • Semantic Flow for Fast and Accurate Scene Parsing
  • Self-Challenging Improves Cross-Domain Generalization
  • Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation
  • Orientation-aware Vehicle Re-identification with Semantics-guided Part Attention Network
  • Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation
  • Towards Streaming Image Understanding
  • ForkGAN: Seeing into the Rainy Night
  • TopoGAN: A Topology-Aware Generative Adversarial Network
  • ExchNet: A Unified Hashing Network for Large-Scale Fine-Grained Image Retrieval
  •  

[Post]

  • Convolutional Occupancy Networks
  • Circumventing Outliers of AutoAugment with Knowledge Distillation
  • TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images
  • GAN Slimming: All-in-One Unified GAN Compression
  • Binarized Neural Network for Single Image Super Resolution
  • Single-Image Depth Prediction Makes Feature Matching Easier
  •  

[Dehazing]

  • Nighttime Defogging Using High-Low Frequency Decomposition and Grayscale-Color Networks
  • HardGAN: A Haze-Aware Representation Distillation GAN for Single Image Dehazing
  • Physics-based Feature Dehazing Networks
  •  

[Enhancement]

  • PieNet: Personalized Image Enhancement Network
  • Multi-level Wavelet-based Generative Adversarial Network for Perceptual Quality Enhancement of Compressed Video
  • Global and Local Enhancement Networks For Paired and Unpaired Image Enhancement
  • Learning Enriched Features for Real Image Restoration and Enhancement
  • Early Exit Or Not: Resource-Efficient Blind Quality Enhancement for Compressed Images
  • Low light video Enhancement using Synthetic Data Produced with an Intermediate Domain Mapping
  • URIE: Universal Image Enhancement for Visual Recognition in the Wild
  • Dynamic Low-light Imaging with Quanta Image Sensors
  •  

[Dinoising]

  • Reconstructing the Noise Manifold for Image Denoising
  • Burst Denoising via Temporally Shifted Wavelet Transforms
  • Robust and On-the-fly Dataset Denoising for Image Classification
  • Learning Graph-Convolutional Representations for Point Cloud Denoising
  • Stochastic Frequency Masking to Improve Super-Resolution and Denoising Networks
  • Spatial-Adaptive Network for Single Image Denoising
  • Unpaired Learning of Deep Blind Image Denoising
  • Spatial Hierarchy Aware Residual Pyramid Network for Time-of-Flight Depth Denoising
  • A Decoupled Learning Scheme for Real-world Burst Denoising from Raw Images
  • Practical Deep Raw Image Denoising on Mobile Devices
  •  

[Deraining]

  • Beyond Monocular Deraining: Paired Rain Removal Networks via Unpaired Semantic Understanding
  • Rethinking Image Deraining via Rain Streaks and Vapors
  • ForkGAN: Seeing into the Rainy Night
  •  

[Event]

  • A Differentiable Recurrent Surface for Asynchronous Event-Based Data
  • Learning Modality Interaction for Temporal Sentence Localization and Event Captioning in Videos
  • Traffic Accident Analysis by Cause and Effect Events Localization
  • How to Train Your Event Camera Neural Network [paper]
  • Entropy Minimisation Framework for Event-based Vision Model Estimation
  • Event-based Asynchronous Sparse Convolutional Networks
  • REMIND Your Neural Network to Prevent Catastrophic Forgetting
  • Learning Event-Driven Video Deblurring and Interpolation
  • Learning to See in the Dark with Events
  • CLAWS: Clustering Assisted Weakly Supervised Learning with Normalcy Suppression for Anomalous Event Detection
  • Stereo Event-based Particle Tracking Velocimetry for 3D Fluid Flow Reconstruction
  • Globally-Optimal Event Camera Motion Estimation
  • Jointly learning visual motion and confidence from local patches in event cameras
  • Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks
  • Event Enhanced High-Quality Image Recovery
  • RhyRNN: Rhythmic RNN for Recognizing Events in Long and Complex Videos
  •  

[Attention]

  • Example-Guided Image Synthesis across Arbitrary Scenes using Masked Spatial-Channel Attention and Self-Supervision
  • Unsupervised Domain Attention Adaptation Network for Caricature Attribute Recognition
  • History Repeats Itself: Human Motion Prediction via Motion Attention
  • CAFE-GAN: Arbitrary Face Attribute Editing with Complementary Attention Feature
  • Supervised Edge Attention Network for Accurate Image Instance Segmentation
  • SPAN: Spatial Pyramid Attention Network for Image Manipulation Detection
  • Forecasting Human-Object Interaction: Joint Prediction of Motor Attention and Actions in First Person Video
  • An Attention-driven Two-stage Clustering Method for Unsupervised Person Re-Identification
  • Spatiotemporal Attention Cell Search for Video Classification
  • Learning Trailer Moments in Full-Length Movies with Co-Contrastive Attention
  • Deep Surface Normal Estimation on the 2-Sphere with Confidence Guided Semantic Attention
  • Attention-Based Query Expansion Learning
  • Attention-Driven Dynamic Graph Convolutional Network for Multi-Label Image Recognition
  • DA4AD: End-to-end Deep Attention Aware Features Aided Visual Localization for Autonomous Driving
  • Few-shot Action Recognition via Permutation-invariant Attention
  • Orientation-aware Vehicle Re-identification with Semantics-guided Part Attention Network
  • Single Image Super-Resolution via a Holistic Attention Network
  • SOLAR: Second-Order Loss and Attention for Image Retrieval
  • GATCluster: Self-Supervised Gaussian-Attention Network for Image Clustering
  • Cross-Attention in Coupled Unmixing Nets for Unsupervised Hyperspectral Super-Resolution
  • Monocular Expressive Body Regression through Body-Driven Attention
  • Deep Reinforced Attention Learning for Quality-Aware Visual Recognition
  • Character Region Attention For Text Spotting
  • Take an Emotion Walk: Perceiving Emotions from Gaits Using Hierarchical Attention Pooling and Affective Mapping
  • End-to-End Low Cost Compressive Spectral Imaging with Spatial-Spectral Self-Attention
  • Spatial Attention Pyramid Network for Unsupervised Domain Adaptation [paper]
  • Semantic Line Detection Using Mirror Attention and Comparative Ranking and Matching
  • Look here! A parametric learning based approach to redirect visual attention
  • Guiding Monocular Depth Estimation Using Depth Attention-Volume
  • Suppressing Mislabeled Data via Grouping and Self-Attention
  • Weight Excitation: Built-in Attention Mechanisms in Convolutional Neural Networks
  • Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation
  • Few-Shot Semantic Segmentation with Democratic Attention Networks
  • Empowering Relational Network by Self-Attention Augmented Conditional Random Fields for Group Activity Recognition
  • AiR: Attention with Reasoning Capability
  • Assembling Modality Representations via Attention Connections
  • Box2Seg: Attention Weighted Loss and Discriminative Feature Learning for Weakly Supervised Segmentation
  • Attention Guided Anomaly Localization in Images
  • ReAD: Reciprocal Attention Discriminator for Image-to-Video Re-Identification
  • Unsupervised Deep Metric Learning with Transformed Attention Consistency and Contrastive Clustering Loss
  • The Devil is in the Details: Self-Supervised Attention for Vehicle Re-Identification
  • Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs
  •  

[Super-Resolution]

  • Component Divide-and-Conquer for Real-World Image Super-Resolution
  • Face Super-Resolution Guided by 3D Facial Priors
  • Learning with Privileged Information for Efficient Image Super-Resolution
  • Fast Adaptation to Super-Resolution Networks via Meta-Learning
  • PlugNet: Degradation Aware Scene Text Recognition Supervised by a Pluggable Super-Resolution Unit
  • Towards Content-independent Multi-Reference Super-Resolution: Adaptive Pattern Matching and Feature Aggregation
  • Single Image Super-Resolution via a Holistic Attention Network
  • SRFlow: Learning the Super-Resolution Space with Normalizing Flow
  • LatticeNet: Towards Lightweight Image Super-resolution with Lattice Block
  • PAMS: Quantized Super-Resolution via Parameterized Max Scale
  • Video Super-Resolution with Recurrent Structure-Detail Network
  • Cross-Attention in Coupled Unmixing Nets for Unsupervised Hyperspectral Super-Resolution
  • Journey Towards Tiny Perceptual Super-Resolution
  • Across Scales & Across Dimensions: Temporal Super-Resolution using Deep Internal Learning
  • Spatial-Angular Interaction for Light Field Image Super-Resolution
  • Mining self-similarity: Label super-resolution with epitomic representations
  • Stochastic Frequency Masking to Improve Super-Resolution and Denoising Networks
  • MuCAN: Multi-Correspondence Aggregation Network for Video Super-Resolution
  • VarSR: Variational Super-Resolution Network for Very Low Resolution Images
  • Texture Hallucination for Large-Factor Painting Super-Resolution
  • Zero-Shot Image Super-Resolution with Depth Guided Internal Degradation Learning
  • Scene Text Image Super-Resolution in the Wild
  • Component Divide-and-Conquer for Real-World Image Super-Resolution、

[Wavelet]

  • Wavelet-Based Dual-Branch Neural Network for Image Demoireing
  • Burst Denoising via Temporally Shifted Wavelet Transforms
  • Multi-level Wavelet-based Generative Adversarial Network for Perceptual Quality Enhancement of Compressed Video
  •  

[Bayesian]

  • Unsupervised Bayesian Deep Learning for Image Reconstruction in Compressive Sensing
  • AABO: Adaptive Anchor Box Optimization for Object Detection via Bayesian Sub-sampling
  •  

[Semantic Segmentation]

  • Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation (oral)
  • Improving Semantic Segmentation via Decoupled Body and Edge Supervision
  • SideInfNet: A Deep Neural Network for Semi-Automatic Semantic Segmentation with Side Information
  • Content-Consistent Matching for Domain Adaptive Semantic Segmentation
  • Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation
  • Efficient Outdoor 3D Point Cloud Semantic Segmentation for Critical Road Objects and Distributed Contexts
  • Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation
  • Virtual Multi-view Fusion for 3D Semantic Segmentation
  • Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation
  • GMNet: Graph Matching Network for Large Scale Part Semantic Segmentation in the Wild
  • Deep FusionNet for Point Cloud Semantic Segmentation
  • Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation
  • Few-Shot Semantic Segmentation with Democratic Attention Networks
  • Prototype Mixture Models for Few-shot Semantic Segmentation
  • Indirect Local Attacks for Context-aware Semantic Segmentation Networks
  • Negative Pseudo Labeling using Class Proportion for Semantic Segmentation in Pathology
  • Part-aware Prototype Network for Few-shot Semantic Segmentation
  • Semi-supervised Semantic Segmentation via Strong-weak Dual-branch Network
  • Self-Prediction for Joint Instance and Semantic Segmentation of Point Clouds
  • Document Structure Extraction using Prior Based HighResolution Hierarchical Semantic Segmentation
  • Learning from Scale-Invariant Examples for Domain Adaptation in Semantic Segmentation
  • Contextual-Relation Consistent Domain Adaptation for Semantic Segmentation
  • Object-Contextual Representations for Semantic Segmentation
  • Learning to Predict Context-adaptive Convolution for Semantic Segmentation
  • Domain Adaptive Semantic Segmentation Using Weak Labels
  • EfficientFCN: Holistically-guided Decoding for Semantic Segmentation
  • Splitting vs. Merging: Mining Object Regions with Discrepancy and Intersection Loss for Weakly Supervised Semantic Segmentation
  • Weakly Supervised Semantic Segmentation with Boundary Exploration
  • Increasing the Robustness of Semantic Segmentation Models with Painting-by-Numbers
  • Class-wise Dynamic Graph Convolution for Semantic Segmentation
  • JSENet: Joint Semantic Segmentation and Edge Detection Network for 3D Point Clouds
  • Tensor Low-Rank Reconstruction for Semantic Segmentation
  • Intra-class Compactness Distillation for Semantic Segmentation
  • SNE-RoadSeg: Incorporating Surface Normal Information into Semantic Segmentation for Accurate Freespace Detection
  • Employing Multi-Estimations for Weakly-Supervised Semantic Segmentation
  •  
  •  

[Distillation]

  • StyleGAN2 Distillation for Feed-forward Image Manipulation
  • Online Ensemble Model Compression using Knowledge Distillation
  • Feature Normalized Knowledge Distillation for Image Classification
  • Knowledge Distillation Meets Self-Supervision
  • Discriminability Distillation in Group Representation Learning
  • Optical Flow Distillation: Towards Efficient and Stable Video Style Transfer
  • Prime-Aware Adaptive Distillation
  • Robust Re-Identification by Multiple Views Knowledge Distillation
  • HardGAN: A Haze-Aware Representation Distillation GAN for Single Image Dehazing
  • DOPE: Distillation Of Part Experts for whole-body 3D pose estimation in the wild
  • Weight Decay Scheduling and Knowledge Distillation for Active Learning
  • Circumventing Outliers of AutoAugment with Knowledge Distillation
  • Semantic Relation Preserving Knowledge Distillation for Image-to-Image Translation
  • Domain Adaptation through Task Distillation
  • Improving Face Recognition from Hard Samples via Distribution Distillation Loss
  • Defocus Blur Detection via Depth Distillation
  • Intra-class Compactness Distillation for Semantic Segmentation
  • Differentiable Feature Aggregation Search for Knowledge Distillation
  • Exclusivity-Consistency Regularized Knowledge Distillation for Face Recognition
  • MetaDistiller: Network Self-boosting via Meta-learned Top-down Distillation
  • Reversing the cycle: self-supervised deep stereo through enhanced monocular distillation
  • Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification
  • Interpretable Foreground Object Search As Knowledge Distillation
  • Improving Knowledge Distillation via Category Structure
  • Local Correlation Consistency for Knowledge Distillation
  • Knowledge Transfer via Dense Cross-layer Mutual-distillation
  • Matching Guided Distillation
  • AMLN: Adversarial-based Mutual Learning Network for Online Knowledge Distillation

 

 

 

 

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