CVPR2020 最全整理:论文汇总 / 代码 / 项目 / 论文解读(更新中)【计算机视觉】

作为计算机视觉领域三大顶会之一,CVPR2020目前已公布了所有接收论文ID,一共有1470篇论文被接收,接收率为22%,相比去年降低3个百分点,竞争越来越激烈,相关报道:1470篇!CVPR2020结果出炉,你中了吗?(附部分论文链接/开源代码/解读)
我们对CVPR2020的优秀论文进行了解读报道技术直播,详见:


同时,我们对CVPR2020的论文做了分类汇总,详见以下列表(持续更新):

此前我们也对CVPR2019的论文做了分类汇总:CVPR2019 最全整理:全部论文下载,GitHub 源码汇总、直播视频、论文解读等。本帖是对CVPR2020顶会论文的实时跟进和分类,欢迎点击文末关注按钮,即可获取本帖最新更新消息。

推荐阅读:



CVPR2020 1467篇论文合集打包下载:
链接: https://pan.baidu.com/s/1E3S0l-5icmpYn5LIq1KL9w 提取码: km9d


目录

1. 目标检测

2. 图像分割

3. 人脸识别

4. 目标跟踪

5. 三维点云/三维重建

6. 图像处理

7. 图像分类

8. 姿态估计/动作识别

9. 视频分析

10. OCR

11. GAN

12. 小样本/零样本

13. 弱监督/无监督/自监督

14. 行人跟踪/行人检测/ReID

15. 神经网络/模型加速/模型压缩

16. 超分辨率

17. 视觉常识/数据集/其他



目标检测

  1. Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection

    论文地址:https://arxiv.org/abs/1912.02424

    代码:https://github.com/sfzhang15/ATSS

  2. Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector

    论文地址:https://arxiv.org/abs/1908.01998

  3. AugFPN: Improving Multi-scale Feature Learning for Object Detection

    论文地址:https://arxiv.org/abs/1912.05384

  4. Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection

    论文地址:https://arxiv.org/abs/2003.11818

    代码:https://github.com/ggjy/HitDet.pytorch

  5. Multi-task Collaborative Network for Joint Referring Expression Comprehension and Segmentation

    论文地址:https://arxiv.org/abs/2003.08813

  6. CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection

    论文地址:https://arxiv.org/abs/2003.09119

    代码:https://github.com/KiveeDong/CentripetalNet



图像分割

  1. Semi-Supervised Semantic Image Segmentation with Self-correcting Networks

    论文地址:https://arxiv.org/abs/1811.07073

  2. Deep Snake for Real-Time Instance Segmentation

    论文地址:https://arxiv.org/abs/2001.01629

  3. CenterMask : Real-Time Anchor-Free Instance Segmentation

    论文地址:https://arxiv.org/abs/1911.06667

    代码:https://github.com/youngwanLEE/CenterMask

  4. SketchGCN: Semantic Sketch Segmentation with Graph Convolutional Networks

    论文地址:https://arxiv.org/abs/2003.00678

  5. PolarMask: Single Shot Instance Segmentation with Polar Representation

    论文地址:https://arxiv.org/abs/1909.13226

    代码:https://github.com/xieenze/PolarMask

  6. xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation

    论文地址:https://arxiv.org/abs/1911.12676

  7. BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation

    论文地址:https://arxiv.org/abs/2001.00309

  8. Enhancing Generic Segmentation with Learned Region Representations

    论文地址:https://arxiv.org/abs/1911.08564



人脸识别

  1. Towards Universal Representation Learning for Deep Face Recognition

    论文地址:https://arxiv.org/abs/2002.11841

  2. Suppressing Uncertainties for Large-Scale Facial Expression Recognition

    论文地址: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

    论文地址:https://arxiv.org/pdf/1912.13458.pdf

  4. Pose Agnostic Cross-spectral Hallucination via Disentangling Independent Factors

    论文地址:https://arxiv.org/abs/1909.04365

  5. Deep Spatial Gradient and Temporal Depth Learning for Face Anti-spoofing

    论文地址:https://arxiv.org/abs/2003.08061

    代码:https://github.com/clks-wzz/FAS-SGTD

  6. Learning Meta Face Recognition in Unseen Domains

    论文地址:https://arxiv.org/abs/2003.07733

    代码:https://github.com/cleardusk/MFR



目标跟踪

  1. ROAM: Recurrently Optimizing Tracking Model

    论文地址:https://arxiv.org/abs/1907.12006



三维点云&重建

  1. PF-Net: Point Fractal Network for 3D Point Cloud Completion

    论文地址:https://arxiv.org/abs/2003.00410

  2. PointAugment: an Auto-Augmentation Framework for Point Cloud Classification

    论文地址:https://arxiv.org/abs/2002.10876

    代码:https://github.com/liruihui/PointAugment/

  3. Learning multiview 3D point cloud registration

    论文地址:https://arxiv.org/abs/2001.05119

  4. C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds

    论文地址:https://arxiv.org/abs/1912.07009

  5. RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds

    论文地址:https://arxiv.org/abs/1911.11236

  6. Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image

    论文地址:https://arxiv.org/abs/2002.12212

  7. Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion

    论文地址:https://arxiv.org/abs/2003.01456

  8. In Perfect Shape: Certifiably Optimal 3D Shape Reconstruction from 2D Landmarks

    论文地址:https://arxiv.org/pdf/1911.11924.pdf

  9. Attentive Context Normalization for Robust Permutation-Equivariant Learning

    论文地址:https://arxiv.org/abs/1907.02545 Weiwei Sun, Wei Jiang, Eduard Trulls, Andrea Tagliasacchi, Kwang Moo Yi

  10. PQ-NET: A Generative Part Seq2Seq Network for 3D Shapes

    论文地址:https://arxiv.org/abs/1911.10949

  11. SG-NN: Sparse Generative Neural Networks for Self-Supervised Scene Completion of RGB-D Scans

    论文地址:https://arxiv.org/abs/1912.00036

  12. Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo Matching

    论文地址:https://arxiv.org/abs/1912.06378

    代码:https://github.com/alibaba/cascade-stereo

  13. Unsupervised Learning of Intrinsic Structural Representation Points

    论文地址:https://arxiv.org/abs/2003.01661

    代码:https://github.com/NolenChen/3DStructurePoints



图像处理

  1. Learning to Shade Hand-drawn Sketches

    论文地址:https://arxiv.org/abs/2002.11812

  2. Single Image Reflection Removal through Cascaded Refinement

    论文地址:https://arxiv.org/abs/1911.06634

  3. Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data

    论文地址:https://arxiv.org/abs/2002.11297

  4. Deep Image Harmonization via Domain Verification

    论文地址:https://arxiv.org/abs/1911.13239

    代码:https://github.com/bcmi/Image_Harmonization_Datasets

  5. RoutedFusion: Learning Real-time Depth Map Fusion

    论文地址:https://arxiv.org/pdf/2001.04388.pdf

  6. Neural Contours: Learning to Draw Lines from 3D Shapes

    论文地址:https://arxiv.org/abs/2003.10333

  7. Towards Photo-Realistic Virtual Try-On by Adaptively Generating鈫Preserving Image Content

    论文地址:https://arxiv.org/abs/2003.05863

  8. Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task(图像处理-图像特征匹配)

    论文地址:https://arxiv.org/abs/1912.00623

  9. Correspondence Networks with Adaptive Neighbourhood Consensus(图像处理-图像特征匹配)

    论文地址:https://arxiv.org/abs/2003.12059

  10. Normalized and Geometry-Aware Self-Attention Network for Image Captioning(图像处理-图像字幕)

    论文地址:https://arxiv.org/abs/2003.08897


图像分类

  1. Self-training with Noisy Student improves ImageNet classification

    论文地址:https://arxiv.org/abs/1911.04252

  2. Image Matching across Wide Baselines: From Paper to Practice

    论文地址:https://arxiv.org/abs/2003.01587

  3. Towards Robust Image Classification Using Sequential Attention Models

    论文地址:https://arxiv.org/abs/1912.02184

  4. Learning in the Frequency Domain

    论文地址:https://arxiv.org/abs/2002.12416

  5. Learning from Web Data with Memory Module

    论文地址:https://arxiv.org/abs/1906.12028

  6. Making Better Mistakes: Leveraging Class Hierarchies with Deep Networks

    论文地址:https://arxiv.org/abs/1912.09393



姿态估计/动作识别

  1. VIBE: Video Inference for Human Body Pose and Shape Estimation

    论文地址:https://arxiv.org/abs/1912.05656

    代码:https://github.com/mkocabas/VIBE

  2. Distribution-Aware Coordinate Representation for Human Pose Estimation

    论文地址:https://arxiv.org/abs/1910.06278

    代码:https://github.com/ilovepose/DarkPose

  3. 4D Association Graph for Realtime Multi-person Motion Capture Using Multiple Video Cameras

    论文地址:https://arxiv.org/abs/2002.12625

  4. Optimal least-squares solution to the hand-eye calibration problem

    论文地址:https://arxiv.org/abs/2002.10838

  5. D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry

    论文地址:https://arxiv.org/abs/2003.01060

  6. Multi-Modal Domain Adaptation for Fine-Grained Action Recognition

    论文地址:https://arxiv.org/abs/2001.09691

  7. Distribution Aware Coordinate Representation for Human Pose Estimation

    论文地址:https://arxiv.org/abs/1910.06278

  8. The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose Estimation

    论文地址:https://arxiv.org/abs/1911.07524

  9. PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimation

    论文地址:https://arxiv.org/abs/1911.04231

  10. Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation

    论文地址:https://arxiv.org/abs/2003.02824

  11. G2L-Net: Global to Local Network for Real-time 6D Pose Estimation with Embedding Vector Features

    论文地址:https://arxiv.org/abs/2003.11089

  12. Deep Image Spatial Transformation for Person Image Generation

    论文地址:https://arxiv.org/abs/2003.00696

    代码:https://github.com/RenYurui/ Global-Flow-Local-Attention



视频分析

  1. Rethinking Zero-shot Video Classification: End-to-end Training for Realistic Applications

    论文地址:https://arxiv.org/abs/2003.01455

    代码:https://github.com/bbrattoli/ZeroShotVideoClassification

  2. Say As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene Graphs

    论文地址:https://arxiv.org/abs/2003.00387

  3. Fine-grained Video-Text Retrieval with Hierarchical Graph Reasoning

    论文地址:https://arxiv.org/abs/2003.00392

  4. Object Relational Graph with Teacher-Recommended Learning for Video Captioning

    论文地址:https://arxiv.org/abs/2002.11566

  5. Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution

    论文地址:https://arxiv.org/abs/2002.11616

  6. Blurry Video Frame Interpolation

    论文地址:https://arxiv.org/abs/2002.12259

  7. Hierarchical Conditional Relation Networks for Video Question Answering

    论文地址:https://arxiv.org/abs/2002.10698

  8. Action Modifiers:Learning from Adverbs in Instructional Video

    论文地址:https://arxiv.org/abs/1912.06617

  9. Visual Grounding in Video for Unsupervised Word Translation

    论文地址:https://arxiv.org/abs/2003.05078

    代码:https://github.com/gsig/visual-grounding

  10. MaskFlownet: Asymmetric Feature Matching with Learnable Occlusion Mask(视频分析-光流估计)

    论文地址:https://arxiv.org/abs/2003.10955

    代码:https://github.com/microsoft/MaskFlownet

  11. Use the Force, Luke! Learning to Predict Physical Forces by Simulating Effects(视频预测)

    论文地址:https://arxiv.org/abs/2003.12045

    代码:https://ehsanik.github.io/forcecvpr2020



OCR

  1. ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network

    论文地址:https://arxiv.org/abs/2002.10200

    代码:https://github.com/Yuliang-Liu/bezier_curve_text_spotting,https://github.com/aim-uofa/adet

2.Iterative Answer Prediction with Pointer-Augmented Multimodal Transformers for TextVQA

论文地址:https://arxiv.org/abs/1911.06258



GAN

  1. Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models

    论文地址:https://arxiv.org/abs/1911.12287

    代码:https://github.com/giannisdaras/ylg

  2. MSG-GAN: Multi-Scale Gradient GAN for Stable Image Synthesis

    论文地址:https://arxiv.org/abs/1903.06048

  3. Robust Design of Deep Neural Networks against Adversarial Attacks based on Lyapunov Theory

    论文地址:https://arxiv.org/abs/1911.04636

4.PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfer

论文地址:https://arxiv.org/abs/1909.06956



小样本/零样本

  1. Improved Few-Shot Visual Classification

    论文地址:https://arxiv.org/pdf/1912.03432.pdf

  2. Meta-Transfer Learning for Zero-Shot Super-Resolution

    论文地址:https://arxiv.org/abs/2002.12213

  3. Instance Credibility Inference for Few-Shot Learning

    论文地址:https://arxiv.org/abs/2003.11853

    代码:https://github.com/Yikai-Wang/ICI-FSL



弱监督/无监督/自监督

  1. Rethinking the Route Towards Weakly Supervised Object Localization

    论文地址:https://arxiv.org/abs/2002.11359

  2. NestedVAE: Isolating Common Factors via Weak Supervision

    论文地址:https://arxiv.org/abs/2002.11576

  3. Unsupervised Reinforcement Learning of Transferable Meta-Skills for Embodied Navigation

    论文地址:https://arxiv.org/abs/1911.07450

  4. Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction

    论文地址:https://arxiv.org/abs/2003.01460

  5. ClusterFit: Improving Generalization of Visual Representations

    论文地址:https://arxiv.org/abs/1912.03330

  6. Auto-Encoding Twin-Bottleneck Hashing

    论文地址:https://arxiv.org/abs/2002.11930

  7. Learning Representations by Predicting Bags of Visual Words

    论文地址:https://arxiv.org/abs/2002.12247

  8. A Characteristic Function Approach to Deep Implicit Generative Modeling

    论文地址:https://arxiv.org/abs/1909.07425

  9. Unsupervised Learning of Intrinsic Structural Representation Points

    论文地址:https://arxiv.org/abs/2003.01661

    代码:https://github.com/NolenChen/3DStructurePoints



行人跟踪/行人检测/ReID

  1. Cross-modality Person re-identification with Shared-Specific Feature Transfer

    论文地址:https://arxiv.org/abs/2002.12489

2.Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction

论文地址:https://arxiv.org/abs/2002.11927

3.The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction

论文地址:https://arxiv.org/abs/1912.06445



神经网络/模型压缩/模型加速

  1. GhostNet: More Features from Cheap Operations

    论文地址:https://arxiv.org/abs/1911.11907

    代码:https://github.com/iamhankai/ghostnet

  2. Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral

    论文地址:https://arxiv.org/abs/2003.01826

  3. GPU-Accelerated Mobile Multi-view Style Transfer

    论文地址:https://arxiv.org/abs/2003.00706

  4. Bundle Adjustment on a Graph Processor

    论文地址:https://arxiv.org/abs/2003.03134

    代码:https://github.com/joeaortiz/gbp

  5. Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral 

    论文地址:https://arxiv.org/abs/2003.01826

  6. Holistically-Attracted Wireframe Parsing

    论文地址:https://arxiv.org/abs/2003.01663

  7. AdderNet: Do We Really Need Multiplications in Deep Learning? 

    论文地址:https://arxiv.org/abs/1912.13200

  8. CARS: Contunuous Evolution for Efficient Neural Architecture Search

    论文地址:https://arxiv.org/abs/1909.04977

    代码:https://github.com/huawei-noah/CARS

  9. Π-nets: Deep Polynomial Neural Networksv

    论文地址:https://arxiv.org/abs/2003.03828

  10. Explaining Knowledge Distillation by Quantifying the Knowledge

    论文地址:https://arxiv.org/abs/2003.03622



超分辨率

  1. Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution

    论文地址:https://arxiv.org/abs/2002.11616

2.Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution

论文地址:https://arxiv.org/abs/2003.07018

代码:https://github.com/guoyongcs/DRN



视觉常识/其他

  1. Visual Commonsense R-CNN

    论文地址:https://arxiv.org/abs/2002.12204

    代码:https://github.com/Wangt-CN/VC-R-CNN

  2. Scalable Uncertainty for Computer Vision with Functional Variational Inference

    论文地址:https://arxiv.org/abs/2003.03396

  3. Deep Representation Learning on Long-tailed Data: A Learnable Embedding Augmentation Perspective

    论文地址:https://arxiv.org/abs/2002.10826

  4. Representations, Metrics and Statistics For Shape Analysis of Elastic Graphs

    论文地址:https://arxiv.org/abs/2003.00287

  5. Filter Grafting for Deep Neural Networks

    论文地址:https://arxiv.org/abs/2001.05868

    代码:https://github.com/fxmeng/filter-grafting.git

  6. 12-in-1: Multi-Task Vision and Language Representation Learning

    论文地址:https://arxiv.org/abs/1912.02315

  7. Towards Learning a Generic Agent for Vision-and-Language Navigation via Pre-training

    论文地址:https://arxiv.org/abs/2002.10638

    代码:https://github.com/weituo12321/PREVALENT

  8. Unbiased Scene Graph Generation from Biased Training

    论文地址:https://arxiv.org/abs/2002.11949

9.Towards Visually Explaining Variational Autoencoders

论文地址:https://arxiv.org/abs/1911.07389

  1. BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition

    论文地址:https://www.weixiushen.com/publication/cvpr20_BBN.pdf

    代码:https://github.com/Megvii-Nanjing/BBN

  2. High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks

    论文地址:https://arxiv.org/abs/1905.13545

  3. SAM: The Sensitivity of Attribution Methods to Hyperparameters

    论文地址:https://s.anhnguyen.me/sam\_cvpr2020.pdf

    代码:https://github.com/anguyen8/sam

  4. Π− nets: Deep Polynomial Neural Networks

    论文地址:https://arxiv.org/abs/2003.03828

  5. Towards Backward-Compatible Representation Learning

    论文地址:https://arxiv.org/abs/2003.11942

  6. On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location

    论文地址:https://arxiv.org/abs/2003.07064

  7. KeypointNet: A Large-scale 3D Keypoint Dataset Aggregated from Numerous Human Annotations(数据集)

    论文地址:https://arxiv.org/abs/2002.12687

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