A list of CVPR 2020 Papers with open-source code, forked and translated from https://github.com/amusi/CVPR2020-Code
- CNN
- Image classification
- Target Detection
- 3D Object Detection
- Video Object Detection
- Target Tracking
- Semantic Segmentation
- Instance Segmentation
- Panorama Segmentation
- Video Target Segmentation
- Super Pixel Segmentation
- NAS
- GAN
- Re-ID
- 3D Point Cloud (Classification/Segmentation/Registration/Tracking, etc.)
- Face (recognition/detection/reconstruction, etc.)
- Human pose estimation (2D/3D)
- Human Body Analysis
- Scene Text Detection
- Scene Text Recognition
- Feature (point) detection and description
- Super Resolution
- Model Compression/Pruning
- Video Understanding/Action Recognition
- Crowd Counting
- Depth Estimation
- 6D target pose estimation
- Gesture estimation
- Saliency detection
- Denoising
- Deblurring
- Dehazing
- Feature point detection and description
- Visual Q&A (VQA)
- Video QA(VideoQA)
- Visual Language Navigation
- Video compression
- Video Insert Frame
- Style Transfer
- Lane Line Detection
- "Human-thing" interactive (HOI) detection
- Track Prediction
- Motion Prediction
- Optical Flow Estimation
- Image retrieval
- Virtual try-on
- HDR
- Anti-sample
- Three-dimensional reconstruction
- Depth Completion
- Semantic Scene Completion
- Image/Video description
- Wireframe Analysis
- Dataset
- OTHER
- Unsure in the middle
Exploring Self-attention for Image Recognition
Improving Convolutional Networks with Self-Calibrated Convolutions
- Homepage: https://mmcheng.net/scconv/
- Paper: http://mftp.mmcheng.net/Papers/20cvprSCNet.pdf
- Code: https://github.com/backseason/SCNet
Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets
Compositional Convolutional Neural Networks: A Deep Architecture with Innate Robustness to Partial Occlusion
Spatially Attentive Output Layer for Image Classification
- Paper: https://arxiv.org/abs/2004.07570
- Code (seems to be deleted by the original author): https://github.com/ildoonet/spatially-attentive-output-layer
AugFPN: Improving Multi-scale Feature Learning for Object Detection
- Paper: http://openaccess.thecvf.com/content_CVPR_2020/papers/Guo_AugFPN_Improving_Multi-Scale_Feature_Learning_for_Object_Detection_CVPR_2020_paper.pdf
- Code: https://github.com/Gus-Guo/AugFPN
Noise-Aware Fully Webly Supervised Object Detection
- Paper: http://openaccess.thecvf.com/content_CVPR_2020/html/Shen_Noise-Aware_Fully_Webly_Supervised_Object_Detection_CVPR_2020_paper.html
- Code: https://github.com/shenyunhang/NA-fWebSOD/
Learning a Unified Sample Weighting Network for Object Detection
D2Det: Towards High Quality Object Detection and Instance Segmentation
- Paper: http://openaccess.thecvf.com/content_CVPR_2020/papers/Cao_D2Det_Towards_High_Quality_Object_Detection_and_Instance_Segmentation_CVPR_2020_paper.pdf
- Code: https://github.com/JialeCao001/D2Det
Dynamic Refinement Network for Oriented and Densely Packed Object Detection
- Link to download the paper: https://arxiv.org/abs/2005.09973
- Code and data set: https://github.com/Anymake/DRN_CVPR2020
Scale-Equalizing Pyramid Convolution for Object Detection
Revisiting the Sibling Head in Object Detector
Scale-equalizing Pyramid Convolution for Object Detection
- Paper: No
- Code: https://github.com/jshilong/SEPC
Detection in Crowded Scenes: One Proposal, Multiple Predictions
Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection
Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection
BiDet: An Efficient Binarized Object Detector
Harmonizing Transferability and Discriminability for Adapting Object Detectors
CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection
Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection
EfficientDet: Scalable and Efficient Object Detection
- Paper: https://arxiv.org/abs/1911.09070
- Code: https://github.com/google/automl/tree/master/efficientdet
Structure Aware Single-stage 3D Object Detection from Point Cloud
- Paper: http://openaccess.thecvf.com/content_CVPR_2020/html/He_Structure_Aware_Single-Stage_3D_Object_Detection_From_Point_Cloud_CVPR_2020_paper.html
- Code: https://github.com/skyhehe123/SA-SSD
IDA-3D: Instance-Depth-Aware 3D Object Detection from Stereo Vision for Autonomous Driving
- Paper: http://openaccess.thecvf.com/content_CVPR_2020/papers/Peng_IDA-3D_Instance-Depth-Aware_3D_Object_Detection_From_Stereo_Vision_for_Autonomous_CVPR_2020_paper.pdf
- Code: https://github.com/swords123/IDA-3D
Train in Germany, Test in The USA: Making 3D Object Detectors Generalize
MLCVNet: Multi-Level Context VoteNet for 3D Object Detection
3DSSD: Point-based 3D Single Stage Object Detector
- CVPR 2020 Oral
- Paper: https://arxiv.org/abs/2002.10187
- Code: https://github.com/tomztyang/3DSSD
Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection
DSGN: Deep Stereo Geometry Network for 3D Object Detection
LiDAR-based Online 3D Video Object Detection with Graph-based Message Passing and Spatiotemporal Transformer Attention
PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud
Memory Enhanced Global-Local Aggregation for Video Object Detection
SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking
D3S -- A Discriminative Single Shot Segmentation Tracker
ROAM: Recurrently Optimizing Tracking Model
Siam R-CNN: Visual Tracking by Re-Detection
- Homepage: https://www.vision.rwth-aachen.de/page/siamrcnn
- Paper: https://arxiv.org/abs/1911.12836
- Paper 2: https://www.vision.rwth-aachen.de/media/papers/192/siamrcnn.pdf
- Code: https://github.com/VisualComputingInstitute/SiamR-CNN
Cooling-Shrinking Attack: Blinding the Tracker with Imperceptible Noises
High-Performance Long-Term Tracking with Meta-Updater
AutoTrack: Towards High-Performance Visual Tracking for UAV with Automatic Spatio-Temporal Regularization
Probabilistic Regression for Visual Tracking
MAST: A Memory-Augmented Self-supervised Tracker
Siamese Box Adaptive Network for Visual Tracking
Super-BPD: Super Boundary-to-Pixel Direction for Fast Image Segmentation
- Paper: No
- Code: https://github.com/JianqiangWan/Super-BPD
Single-Stage Semantic Segmentation from Image Labels
Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation
- Paper: https://arxiv.org/abs/2003.00867
- Code: https://github.com/MyeongJin-Kim/Learning-Texture-Invariant-Representation
MSeg: A Composite Dataset for Multi-domain Semantic Segmentation
CascadePSP: Toward Class-Agnostic and Very High-Resolution Segmentation via Global and Local Refinement
Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision
- Oral
- Paper: https://arxiv.org/abs/2004.07703
- Code: https://github.com/feipan664/IntraDA
Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation
Temporally Distributed Networks for Fast Video Segmentation
Context Prior for Scene Segmentation
Strip Pooling: Rethinking Spatial Pooling for Scene Parsing
Cars Can't Fly up in the Sky: Improving Urban-Scene Segmentation via Height-driven Attention Networks
Learning Dynamic Routing for Semantic Segmentation
D2Det: Towards High Quality Object Detection and Instance Segmentation
- Paper: http://openaccess.thecvf.com/content_CVPR_2020/papers/Cao_D2Det_Towards_High_Quality_Object_Detection_and_Instance_Segmentation_CVPR_2020_paper.pdf
- Code: https://github.com/JialeCao001/D2Det
PolarMask: Single Shot Instance Segmentation with Polar Representation
- Paper: https://arxiv.org/abs/1909.13226
- Code: https://github.com/xieenze/PolarMask
- Interpretation: https://zhuanlan.zhihu.com/p/84890413
CenterMask: Real-Time Anchor-Free Instance Segmentation
BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation
Deep Snake for Real-Time Instance Segmentation
Mask Encoding for Single Shot Instance Segmentation
Pixel Consensus Voting for Panoptic Segmentation
- Paper: https://arxiv.org/abs/2004.01849
- Code: Not yet announced
BANet: Bidirectional Aggregation Network with Occlusion Handling for Panoptic Segmentation
A Transductive Approach for Video Object Segmentation
State-Aware Tracker for Real-Time Video Object Segmentation
Learning Fast and Robust Target Models for Video Object Segmentation
Learning Video Object Segmentation from Unlabeled Videos
Superpixel Segmentation with Fully Convolutional Networks
AOWS: Adaptive and optimal network width search with latency constraints
Densely Connected Search Space for More Flexible Neural Architecture Search
MTL-NAS: Task-Agnostic Neural Architecture Search towards General-Purpose Multi-Task Learning
FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions
- Link to download the paper: https://arxiv.org/abs/2004.05565
- Code: https://github.com/facebookresearch/mobile-vision
Neural Architecture Search for Lightweight Non-Local Networks
Rethinking Performance Estimation in Neural Architecture Search
- Paper: https://arxiv.org/abs/2005.09917
- Code: https://github.com/zhengxiawu/rethinking_performance_estimation_in_NAS
- Interpretation 1: https://www.zhihu.com/question/372070853/answer/1035234510
- Interpretation 2: https://zhuanlan.zhihu.com/p/111167409
CARS: Continuous Evolution for Efficient Neural Architecture Search
- Paper: https://arxiv.org/abs/1909.04977
- Code (open source soon): https://github.com/huawei-noah/CARS
Distribution-induced Bidirectional Generative Adversarial Network for Graph Representation Learning
PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfer
Semantically Mutil-modal Image SynPaper
- Homepage: http://seanseattle.github.io/SMIS
- Paper: https://arxiv.org/abs/2003.12697
- Code: https://github.com/Seanseattle/SMIS
Unpaired Portrait Drawing Generation via Asymmetric Cycle Mapping
- Paper: https://yiranran.github.io/files/CVPR2020_Unpaired%20Portrait%20Drawing%20Generation%20via%20Asymmetric%20Cycle%20Mapping.pdf
- Code: https://github.com/yiranran/Unpaired-Portrait-Drawing
Learning to Cartoonize Using White-box Cartoon Representations
- Paper: https://github.com/SystemErrorWang/White-box-Cartoonization/blob/master/paper/06791.pdf
- Homepage: https://systemerrorwang.github.io/White-box-Cartoonization/
- Code: https://github.com/SystemErrorWang/White-box-Cartoonization
- Interpretation: https://zhuanlan.zhihu.com/p/117422157
- Demo video: https://www.bilibili.com/video/av56708333
GAN Compression: Efficient Architectures for Interactive Conditional GANs
Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral Distributions
COCAS: A Large-Scale Clothes Changing Person Dataset for Re-identification
- Paper: https://arxiv.org/abs/2005.07862
- Data set: No
Transferable, Controllable, and Inconspicuous Adversarial Attacks on Person Re-identification With Deep Mis-Ranking
- Paper: https://arxiv.org/abs/2004.04199
- Code: https://github.com/whj363636/Adversarial-attack-on-Person-ReID-With-Deep-Mis-Ranking
Pose-guided Visible Part Matching for Occluded Person ReID
Weakly supervised discriminative feature learning with state information for person identification
PointASNL: Robust Point Clouds Processing using Nonlocal Neural Networks with Adaptive Sampling
Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds
- Link to download the paper: https://arxiv.org/abs/2003.12971
- Code: https://github.com/raoyongming/PointGLR
Grid-GCN for Fast and Scalable Point Cloud Learning
FPConv: Learning Local Flattening for Point Convolution
PointAugment: an Auto-Augmentation Framework for Point Cloud Classification
- Paper: https://arxiv.org/abs/2002.10876
- Code (open source soon): https://github.com/liruihui/PointAugment/
RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds
- Paper: https://arxiv.org/abs/1911.11236
- Code: https://github.com/QingyongHu/RandLA-Net
- Interpretation: https://zhuanlan.zhihu.com/p/105433460
Weakly Supervised Semantic Point Cloud Segmentation: Towards 10X Fewer Labels
PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation
Learning to Segment 3D Point Clouds in 2D Image Space
- Paper: https://arxiv.org/abs/2003.05593
- Code: https://github.com/WPI-VISLab/Learning-to-Segment-3D-Point-Clouds-in-2D-Image-Space
PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation
D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features
RPM-Net: Robust Point Matching using Learned Features
Cascaded Refinement Network for Point Cloud Completion
- Paper: https://arxiv.org/abs/2004.03327
- Code: https://github.com/xiaogangw/cascaded-point-completion
P2B: Point-to-Box Network for 3D Object Tracking in Point Clouds
CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition
Learning Meta Face Recognition in Unseen Domains
- Paper: https://arxiv.org/abs/2003.07733
- Code: https://github.com/cleardusk/MFR
- Interpretation: https://mp.weixin.qq.com/s/YZoEnjpnlvb90qSI3xdJqQ
Searching Central Difference Convolutional Networks for Face Anti-Spoofing
Suppressing Uncertainties for Large-Scale Facial Expression Recognition
- Paper: https://arxiv.org/abs/2002.10392
- Code (open source soon): https://github.com/kaiwang960112/Self-Cure-Network
Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Images
AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"
- Paper: https://arxiv.org/abs/2003.13845
- Data set: https://github.com/lattas/AvatarMe
FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
- Paper: https://arxiv.org/abs/1908.10357
- Code: https://github.com/HRNet/HigherHRNet-Human-Pose-Estimation
The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose Estimation
- Paper: https://arxiv.org/abs/1911.07524
- Code: https://github.com/HuangJunJie2017/UDP-Pose
- Interpretation: https://zhuanlan.zhihu.com/p/92525039
Distribution-Aware Coordinate Representation for Human Pose Estimation
- Homepage: https://ilovepose.github.io/coco/
- Paper: https://arxiv.org/abs/1910.06278
- Code: https://github.com/ilovepose/DarkPose
Fusing Wearable IMUs with Multi-View Images for Human Pose Estimation: A Geometric Approach
- Homepage: https://www.zhe-zhang.com/cvpr2020
- Paper: https://arxiv.org/abs/2003.11163
- Code: https://github.com/CHUNYUWANG/imu-human-pose-pytorch
Bodies at Rest: 3D Human Pose and Shape Estimation from a Pressure Image using Synthetic Data
- Link to download the paper: https://arxiv.org/abs/2004.01166
- Code: https://github.com/Healthcare-Robotics/bodies-at-rest
- Data set: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/KOA4ML
Self-Supervised 3D Human Pose Estimation via Part Guided Novel Image SynPaper
- Homepage: http://val.cds.iisc.ac.in/pgp-human/
- Paper: https://arxiv.org/abs/2004.04400
Compressed Volumetric Heatmaps for Multi-Person 3D Pose Estimation
VIBE: Video Inference for Human Body Pose and Shape Estimation
Back to the Future: Joint Aware Temporal Deep Learning 3D Human Pose Estimation
Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS
- Paper: https://arxiv.org/abs/2003.03972
- Data set: No
Correlating Edge, Pose with Parsing
ContourNet: Taking a Further Step Toward Accurate Arbitrary-Shaped Scene Text Detection
- Paper: http://openaccess.thecvf.com/content_CVPR_2020/papers/Wang_ContourNet_Taking_a_Further_Step_Toward_Accurate_Arbitrary-Shaped_Scene_Text_CVPR_2020_paper.pdf
- Code: https://github.com/wangyuxin87/ContourNet
UnrealText: Synthesizing Realistic Scene Text Images from the Unreal World
- Paper: https://arxiv.org/abs/2003.10608
- Code and data set: https://github.com/Jyouhou/UnrealText/
ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network
- Paper: https://arxiv.org/abs/2002.10200
- Code (open source soon): https://github.com/Yuliang-Liu/bezier_curve_text_spotting
- Code (open source soon): https://github.com/aim-uofa/adet
Deep Relational Reasoning Graph Network for Arbitrary Shape Text Detection
SEED: Semantics Enhanced Encoder-Decoder Framework for Scene Text Recognition
UnrealText: Synthesizing Realistic Scene Text Images from the Unreal World
- Paper: https://arxiv.org/abs/2003.10608
- Code and data set: https://github.com/Jyouhou/UnrealText/
ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network
- Paper: https://arxiv.org/abs/2002.10200
- Code (open source soon): https://github.com/aim-uofa/adet
Learn to Augment: Joint Data Augmentation and Network Optimization for Text Recognition
SuperGlue: Learning Feature Matching with Graph Neural Networks
- Paper: https://arxiv.org/abs/1911.11763
- Code: https://github.com/magicleap/SuperGluePretrainedNetwork
Closed-Loop Matters: Dual Regression Networks for Single Image Super-Resolution
- Paper: http://openaccess.thecvf.com/content_CVPR_2020/html/Guo_Closed-Loop_Matters_Dual_Regression_Networks_for_Single_Image_Super-Resolution_CVPR_2020_paper.html
- Code: https://github.com/guoyongcs/DRN
Learning Texture Transformer Network for Image Super-Resolution
Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining
- Paper: https://arxiv.org/abs/2006.01424
- Code: https://github.com/SHI-Labs/Cross-Scale-Non-Local-Attention
Structure-Preserving Super Resolution with Gradient Guidance
Rethinking Data Augmentation for Image Super-resolution: A Comprehensive Analysis and a New Strategy
TDAN: Temporally-Deformable Alignment Network for Video Super-Resolution
Space-Time-Aware Multi-Resolution Video Enhancement
- Homepage: https://alterzero.github.io/projects/STAR.html
- Paper: http://arxiv.org/abs/2003.13170
- Code: https://github.com/alterzero/STARnet
Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution
DMCP: Differentiable Markov Channel Pruning for Neural Networks
Forward and Backward Information Retention for Accurate Binary Neural Networks
Towards Efficient Model Compression via Learned Global Ranking
HRank: Filter Pruning using High-Rank Feature Map
GAN Compression: Efficient Architectures for Interactive Conditional GANs
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression
Oops! Predicting Unintentional Action in Video
- Homepage: https://oops.cs.columbia.edu/
- Paper: https://arxiv.org/abs/1911.11206
- Code: https://github.com/cvlab-columbia/oops
- Data set: https://oops.cs.columbia.edu/data
PREDICT & CLUSTER: Unsupervised Skeleton Based Action Recognition
Intra- and Inter-Action Understanding via Temporal Action Parsing
- Paper: https://arxiv.org/abs/2005.10229
- Homepage and data set: https://sdolivia.github.io/TAPOS/
3DV: 3D Dynamic Voxel for Action Recognition in Depth Video
FineGym: A Hierarchical Video Dataset for Fine-grained Action Understanding
- Homepage: https://sdolivia.github.io/FineGym/
- Paper: https://arxiv.org/abs/2004.06704
TEA: Temporal Excitation and Aggregation for Action Recognition
X3D: Expanding Architectures for Efficient Video Recognition
Temporal Pyramid Network for Action Recognition
- Home page:https://decisionforce.github.io/TPN
- Paper:https://arxiv.org/abs/2004.03548
- Code:https://github.com/decisionforce/TPN
Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition
BiFuse: Monocular 360◦ Depth Estimation via Bi-Projection Fusion
- Paper:http://openaccess.thecvf.com/content_CVPR_2020/papers/Wang_BiFuse_Monocular_360_Depth_Estimation_via_Bi-Projection_Fusion_CVPR_2020_paper.pdf
- Code:https://github.com/Yeh-yu-hsuan/BiFuse
Focus on defocus: bridging the synthetic to real domain gap for depth estimation
Bi3D: Stereo Depth Estimation via Binary Classifications
AANet: Adaptive Aggregation Network for Efficient Stereo Matching
Towards Better Generalization: Joint Depth-Pose Learning without PoseNet
On the uncertainty of self-supervised monocular depth estimation
3D Packing for Self-Supervised Monocular Depth Estimation
- Paper:https://arxiv.org/abs/1905.02693
- Code:https://github.com/TRI-ML/packnet-sfm
- Demo视频:https://www.bilibili.com/video/av70562892/
Domain Decluttering: Simplifying Images to Mitigate Synthetic-Real Domain Shift and Improve Depth Estimation
MoreFusion: Multi-object Reasoning for 6D Pose Estimation from Volumetric Fusion
EPOS: Estimating 6D Pose of Objects with Symmetries
- Home page:http://cmp.felk.cvut.cz/epos
- Paper:https://arxiv.org/abs/2004.00605
G2L-Net: Global to Local Network for Real-time 6D Pose Estimation with Embedding Vector Features
HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation
Monocular Real-time Hand Shape and Motion Capture using Multi-modal Data
JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection
UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders
- Home page:http://dpfan.net/d3netbenchmark/
- Paper:https://arxiv.org/abs/2004.05763
- Code:https://github.com/JingZhang617/UCNet
A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising
CycleISP: Real Image Restoration via Improved Data SynPaper
Multi-Scale Progressive Fusion Network for Single Image Deraining
Cascaded Deep Video Deblurring Using Temporal Sharpness Prior
- Home page:https://csbhr.github.io/projects/cdvd-tsp/index.html
- Paper:https://arxiv.org/abs/2004.02501
- Code:https://github.com/csbhr/CDVD-TSP
Multi-Scale Boosted Dehazing Network with Dense Feature Fusion
ASLFeat: Learning Local Features of Accurate Shape and Localization
VC R-CNN:Visual Commonsense R-CNN
Hierarchical Conditional Relation Networks for Video Question Answering
Towards Learning a Generic Agent for Vision-and-Language Navigation via Pre-training
- Paper:https://arxiv.org/abs/2002.10638
- Code(soon):https://github.com/weituo12321/PREVALENT
Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement
FeatureFlow: Robust Video Interpolation via Structure-to-Texture Generation
- Paper:http://openaccess.thecvf.com/content_CVPR_2020/html/Gui_FeatureFlow_Robust_Video_Interpolation_via_Structure-to-Texture_Generation_CVPR_2020_paper.html
- Code:https://github.com/CM-BF/FeatureFlow
Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution
Space-Time-Aware Multi-Resolution Video Enhancement
- Home page:https://alterzero.github.io/projects/STAR.html
- Paper:http://arxiv.org/abs/2003.13170
- Code:https://github.com/alterzero/STARnet
Scene-Adaptive Video Frame Interpolation via Meta-Learning
Softmax Splatting for Video Frame Interpolation
- Home page:http://sniklaus.com/papers/softsplat
- Paper:https://arxiv.org/abs/2003.05534
- Code:https://github.com/sniklaus/softmax-splatting
Diversified Arbitrary Style Transfer via Deep Feature Perturbation
Collaborative Distillation for Ultra-Resolution Universal Style Transfer
- Paper:https://arxiv.org/abs/2003.08436
- Code:https://github.com/mingsun-tse/collaborative-distillation
Inter-Region Affinity Distillation for Road Marking Segmentation
PPDM: Parallel Point Detection and Matching for Real-time Human-Object Interaction Detection
Detailed 2D-3D Joint Representation for Human-Object Interaction
Cascaded Human-Object Interaction Recognition
VSGNet: Spatial Attention Network for Detecting Human Object Interactions Using Graph Convolutions
The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction
- Paper:https://arxiv.org/abs/1912.06445
- Code:https://github.com/JunweiLiang/Multiverse
- Dataset:https://next.cs.cmu.edu/multiverse/
Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction
Collaborative Motion Prediction via Neural Motion Message Passing
MotionNet: Joint Perception and Motion Prediction for Autonomous Driving Based on Bird's Eye View Maps
Learning by Analogy: Reliable Supervision from Transformations for Unsupervised Optical Flow Estimation
Evade Deep Image Retrieval by Stashing Private Images in the Hash Space
- Paper:http://openaccess.thecvf.com/content_CVPR_2020/html/Xiao_Evade_Deep_Image_Retrieval_by_Stashing_Private_Images_in_the_CVPR_2020_paper.html
- Code:https://github.com/sugarruy/hashstash
Towards Photo-Realistic Virtual Try-On by Adaptively Generating↔Preserving Image Content
Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline
- Home page:https://www.cmlab.csie.ntu.edu.tw/~yulunliu/SingleHDR
- Paper:https://www.cmlab.csie.ntu.edu.tw/~yulunliu/SingleHDR_/00942.pdf
- Code:https://github.com/alex04072000/SingleHDR
Towards Large yet Imperceptible Adversarial Image Perturbations with Perceptual Color Distance
Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild
- CVPR 2020 Best Paper
- Home page:https://elliottwu.com/projects/unsup3d/
- Paper:https://arxiv.org/abs/1911.11130
- Code:https://github.com/elliottwu/unsup3d
Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization
- Home page:https://shunsukesaito.github.io/PIFuHD/
- Paper:https://arxiv.org/abs/2004.00452
- Code:https://github.com/facebookresearch/pifuhd
Uncertainty-Aware CNNs for Depth Completion: Uncertainty from Beginning to End
3D Sketch-aware Semantic Scene Completion via Semi-supervised Structure Prior
Syntax-Aware Action Targeting for Video Captioning
- Paper:http://openaccess.thecvf.com/content_CVPR_2020/papers/Zheng_Syntax-Aware_Action_Targeting_for_Video_Captioning_CVPR_2020_paper.pdf
- Code:https://github.com/SydCaption/SAAT
Holistically-Attracted Wireframe Parser
- Paper:http://openaccess.thecvf.com/content_CVPR_2020/html/Xue_Holistically-Attracted_Wireframe_Parsing_CVPR_2020_paper.html
- Code:https://github.com/cherubicXN/hawp
Oops! Predicting Unintentional Action in Video
- Home page:https://oops.cs.columbia.edu/
- Paper:https://arxiv.org/abs/1911.11206
- Code:https://github.com/cvlab-columbia/oops
- dataset:https://oops.cs.columbia.edu/data
The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction
- Paper:https://arxiv.org/abs/1912.06445
- Code:https://github.com/JunweiLiang/Multiverse
- dataset:https://next.cs.cmu.edu/multiverse/
Open Compound Domain Adaptation
- Home page:https://liuziwei7.github.io/projects/CompoundDomain.html
- dataset:https://drive.google.com/drive/folders/1_uNTF8RdvhS_sqVTnYx17hEOQpefmE2r?usp=sharing
- Paper:https://arxiv.org/abs/1909.03403
- Code:https://github.com/zhmiao/OpenCompoundDomainAdaptation-OCDA
Intra- and Inter-Action Understanding via Temporal Action Parsing
- Paper:https://arxiv.org/abs/2005.10229
- Home page和dataset:https://sdolivia.github.io/TAPOS/
Dynamic Refinement Network for Oriented and Densely Packed Object Detection
COCAS: A Large-Scale Clothes Changing Person Dataset for Re-identification
- Paper:https://arxiv.org/abs/2005.07862
- dataset:no
KeypointNet: A Large-scale 3D Keypoint Dataset Aggregated from Numerous Human Annotations
MSeg: A Composite Dataset for Multi-domain Semantic Segmentation
- Paper:http://vladlen.info/papers/MSeg.pdf
- Code:https://github.com/mseg-dataset/mseg-api
- dataset:https://github.com/mseg-dataset/mseg-semantic
AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"
Learning to Autofocus
- Paper:https://arxiv.org/abs/2004.12260
- dataset:no
FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction
Bodies at Rest: 3D Human Pose and Shape Estimation from a Pressure Image using Synthetic Data
- Paper:https://arxiv.org/abs/2004.01166
- Code:https://github.com/Healthcare-Robotics/bodies-at-rest
- dataset:https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/KOA4ML
FineGym: A Hierarchical Video Dataset for Fine-grained Action Understanding
- Home page:https://sdolivia.github.io/FineGym/
- Paper:https://arxiv.org/abs/2004.06704
A Local-to-Global Approach to Multi-modal Movie Scene Segmentation
- Home page:https://anyirao.com/projects/SceneSeg.html
- Paper:https://arxiv.org/abs/2004.02678
- Code:https://github.com/AnyiRao/SceneSeg
Deep Homography Estimation for Dynamic Scenes
Assessing Image Quality Issues for Real-World Problems
- Home page:https://vizwiz.org/tasks-and-datasets/image-quality-issues/
- Paper:https://arxiv.org/abs/2003.12511
UnrealText: Synthesizing Realistic Scene Text Images from the Unreal World
- Paper:https://arxiv.org/abs/2003.10608
- Code和dataset:https://github.com/Jyouhou/UnrealText/
PANDA: A Gigapixel-level Human-centric Video Dataset
IntrA: 3D Intracranial Aneurysm Dataset for Deep Learning
Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS
- Paper:https://arxiv.org/abs/2003.03972
- dataset:no
CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus
- Paper:http://openaccess.thecvf.com/content_CVPR_2020/html/Kluger_CONSAC_Robust_Multi-Model_Fitting_by_Conditional_Sample_Consensus_CVPR_2020_paper.html
- Code:https://github.com/fkluger/consac
Learning to Learn Single Domain Generalization
Open Compound Domain Adaptation
- Home page:https://liuziwei7.github.io/projects/CompoundDomain.html
- dataset:https://drive.google.com/drive/folders/1_uNTF8RdvhS_sqVTnYx17hEOQpefmE2r?usp=sharing
- Paper:https://arxiv.org/abs/1909.03403
- Code:https://github.com/zhmiao/OpenCompoundDomainAdaptation-OCDA
Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision
- Paper:http://www.cvlibs.net/publications/Niemeyer2020CVPR.pdf
- Code:https://github.com/autonomousvision/differentiable_volumetric_rendering
QEBA: Query-Efficient Boundary-Based Blackbox Attack
Equalization Loss for Long-Tailed Object Recognition
Instance-aware Image Colorization
- Home page:https://ericsujw.github.io/InstColorization/
- Paper:https://arxiv.org/abs/2005.10825
- Code:https://github.com/ericsujw/InstColorization
Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting
- Paper:https://arxiv.org/abs/2005.09704
- Code:https://github.com/Atlas200dk/sample-imageinpainting-HiFill
Where am I looking at? Joint Location and Orientation Estimation by Cross-View Matching
- Paper:https://arxiv.org/abs/2005.03860
- Code:https://github.com/shiyujiao/cross_view_localization_DSM
Epipolar Transformers
Bringing Old Photos Back to Life
- Home page:http://raywzy.com/Old_Photo/
- Paper:https://arxiv.org/abs/2004.09484
MaskFlownet: Asymmetric Feature Matching with Learnable Occlusion Mask
Self-Supervised Viewpoint Learning from Image Collections
- Paper:https://arxiv.org/abs/2004.01793
- Paper2:https://research.nvidia.com/sites/default/files/pubs/2020-03_Self-Supervised-Viewpoint-Learning/SSV-CVPR2020.pdf
- Code:https://github.com/NVlabs/SSV
Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations
- Oral
- Paper:https://arxiv.org/abs/2003.12237
- Code:https://github.com/cuishuhao/BNM
Towards Learning Structure via Consensus for Face Segmentation and Parsing
Plug-and-Play Algorithms for Large-scale Snapshot Compressive Imaging
- Oral
- Paper:https://arxiv.org/abs/2003.13654
- Code:https://github.com/liuyang12/PnP-SCI
Lightweight Photometric Stereo for Facial Details Recovery
Footprints and Free Space from a Single Color Image
Self-Supervised Monocular Scene Flow Estimation
Quasi-Newton Solver for Robust Non-Rigid Registration
A Local-to-Global Approach to Multi-modal Movie Scene Segmentation
- Home page:https://anyirao.com/projects/SceneSeg.html
- Paper下载链接:https://arxiv.org/abs/2004.02678
- Code:https://github.com/AnyiRao/SceneSeg
DeepFLASH: An Efficient Network for Learning-based Medical Image Registration
Self-Supervised Scene De-occlusion
- Home page:https://xiaohangzhan.github.io/projects/deocclusion/
- Paper:https://arxiv.org/abs/2004.02788
- Code:https://github.com/XiaohangZhan/deocclusion
Polarized Reflection Removal with Perfect Alignment in the Wild
- Home page:https://leichenyang.weebly.com/project-polarized.html
- Code:https://github.com/ChenyangLEI/CVPR2020-Polarized-Reflection-Removal-with-Perfect-Alignment
Background Matting: The World is Your Green Screen
What Deep CNNs Benefit from Global Covariance Pooling: An Optimization Perspective
Look-into-Object: Self-supervised Structure Modeling for Object Recognition
- Paper:no
- Code:https://github.com/JDAI-CV/LIO
Video Object Grounding using Semantic Roles in Language Description
Dynamic Hierarchical Mimicking Towards Consistent Optimization Objectives
SDFDiff: Differentiable Rendering of Signed Distance Fields for 3D Shape Optimization
- Paper:http://www.cs.umd.edu/~yuejiang/papers/SDFDiff.pdf
- Code:https://github.com/YueJiang-nj/CVPR2020-SDFDiff
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location
GhostNet: More Features from Cheap Operations
AdderNet: Do We Really Need Multiplications in Deep Learning?
Deep Image Harmonization via Domain Verification
Blurry Video Frame Interpolation
Extremely Dense Point Correspondences using a Learned Feature Descriptor
- Paper:https://arxiv.org/abs/2003.00619
- Code:https://github.com/lppllppl920/DenseDescriptorLearning-Pytorch
Filter Grafting for Deep Neural Networks
- Paper:https://arxiv.org/abs/2001.05868
- Code:https://github.com/fxmeng/filter-grafting
- Paper:https://www.zhihu.com/question/372070853/answer/1041569335
Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation
Detecting Attended Visual Targets in Video
Deep Image Spatial Transformation for Person Image Generation
Rethinking Zero-shot Video Classification: End-to-end Training for Realistic Applications
- Paper:https://arxiv.org/abs/2003.01455
- Code:https://github.com/bbrattoli/ZeroShotVideoClassification
https://github.com/charlesCXK/3D-SketchAware-SSC
https://github.com/Anonymous20192020/Anonymous_CVPR5767
https://github.com/avirambh/ScopeFlow
https://github.com/csbhr/CDVD-TSP
https://github.com/ymcidence/TBH
https://github.com/yaoyao-liu/mnemonics
https://github.com/meder411/Tangent-Images
https://github.com/KaihuaTang/Scene-Graph-Benchmark.pytorch
https://github.com/sjmoran/deep_local_parametric_filters
https://github.com/charlesCXK/3D-SketchAware-SSC
https://github.com/bermanmaxim/AOWS
https://github.com/dc3ea9f/look-into-object
FADNet: A Fast and Accurate Network for Disparity Estimation
- Paper:n/a
- Code:https://github.com/HKBU-HPML/FADNet
https://github.com/rFID-submit/RandomFID:Not sure
https://github.com/JackSyu/AE-MSR:Not sure
https://github.com/fastconvnets/cvpr2020:Not sure
https://github.com/aimagelab/meshed-memory-transformer:Not sure
https://github.com/TWSFar/CRGNet:Not sure
https://github.com/CVPR-2020/CDARTS:Not sure
https://github.com/anucvml/ddn-cvprw2020:Not sure
https://github.com/dl-model-recommend/model-trust:Not sure
https://github.com/apratimbhattacharyya18/CVPR-2020-Corr-Prior:Not sure
https://github.com/onetcvpr/O-Net:Not sure
https://github.com/502463708/Microcalcification_Detection:Not sure
https://github.com/anonymous-for-review/cvpr-2020-deep-smoke-machine:Not sure
https://github.com/anonymous-for-review/cvpr-2020-smoke-recognition-dataset:Not sure
https://github.com/cvpr-nonrigid/dataset:Not sure
https://github.com/theFool32/PPBA:Not sure
https://github.com/Realtime-Action-Recognition/Realtime-Action-Recognition