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CVPR2020 论文已经在官网上线了！大会6天后正式开始

http://openaccess.thecvf.com/CVPR2020.py

我们对部分论文进行了分类（见下），并下载了所有篇论文

在公众号后台回复：CVPR2020，即可下载所有1470 篇论文，共2.5G

人脸检测/识别/重建

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

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

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

CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition
论文：https://arxiv.org/abs/2004.00288
代码：https://github.com/HuangYG123/CurricularFace

Learning Meta Face Recognition in Unseen Domains
论文：https://arxiv.org/abs/2003.07733
代码：https://github.com/cleardusk/MFR

Searching Central Difference Convolutional Networks for Face Anti-Spoofing
论文：https://arxiv.org/abs/2003.04092
代码：https://github.com/ZitongYu/CDCN

Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Images
论文：https://arxiv.org/abs/2003.08124
代码：https://github.com/Hangz-nju-cuhk/Rotate-and-Render

AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"
论文：https://arxiv.org/abs/2003.13845
代码：https://github.com/lattas/AvatarMe

FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction
论文：https://arxiv.org/abs/2003.13989
代码：https://github.com/zhuhao-nju/facescape

目标检测/分割/跟踪

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

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

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

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

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

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

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

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

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

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

图像处理

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

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

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

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

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

图像分类

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

Spatially Attentive Output Layer for Image Classification
https://arxiv.org/abs/2004.07570

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

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

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

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

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

视频内容分析
Hierarchical Conditional Relation Networks for Video Question Answering
论文：https://arxiv.org/abs/2002.10698

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

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

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

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

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

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

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

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

3DV: 3D Dynamic Voxel for Action Recognition in Depth Video
论文：https://arxiv.org/abs/2005.05501
代码：https://github.com/3huo/3DV-Action

FineGym: A Hierarchical Video Dataset for Fine-grained Action Understanding
主页：https://sdolivia.github.io/FineGym/
论文：https://arxiv.org/abs/2004.06704

人体关键点检测/姿态估计

Correlating Edge, Pose with Parsing
论文：https://arxiv.org/abs/2005.01431
代码：https://github.com/ziwei-zh/CorrPM

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

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

Self-Supervised 3D Human Pose Estimation via Part Guided Novel Image Synthesis
论文：https://arxiv.org/abs/2004.04400

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

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

Bodies at Rest: 3D Human Pose and Shape Estimation from a Pressure Image using Synthetic Data
论文：https://arxiv.org/abs/2004.01166
代码：https://github.com/Healthcare-Robotics/bodies-at-rest

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

Back to the Future: Joint Aware Temporal Deep Learning 3D Human Pose Estimation
论文：https://arxiv.org/abs/2002.11251
代码：https://github.com/vnmr/JointVideoPose3D

Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS
论文：https://arxiv.org/abs/2003.03972

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

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

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

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

DMCP: Differentiable Markov Channel Pruning for Neural Networks
论文：https://arxiv.org/abs/2005.03354
代码：https://github.com/zx55/dmcp

Forward and Backward Information Retention for Accurate Binary Neural Networks
论文：https://arxiv.org/abs/1909.10788
代码：https://github.com/htqin/IR-Net

Towards Efficient Model Compression via Learned Global Ranking
论文：https://arxiv.org/abs/1904.12368
代码：https://github.com/cmu-enyac/LeGR

HRank: Filter Pruning using High-Rank Feature Map
论文：http://arxiv.org/abs/2002.10179
代码：https://github.com/lmbxmu/HRank

GAN Compression: Efficient Architectures for Interactive Conditional GANs
论文：https://arxiv.org/abs/2003.08936
代码：https://github.com/mit-han-lab/gan-compression

Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression
论文：https://arxiv.org/abs/2003.08935
代码：https://github.com/ofsoundof/group_sparsity

神经网络架构设计和搜索NAS

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

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

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

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

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

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

生成对抗GAN

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

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

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

Towards Large yet Imperceptible Adversarial Image Perturbations with Perceptual Color Distance
论文：https://arxiv.org/abs/1911.02466
代码：https://github.com/ZhengyuZhao/PerC-Adversarial

点云/3D重建/SLAM

D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features
论文：https://arxiv.org/abs/2003.03164
代码：https://github.com/XuyangBai/D3Feat

RPM-Net: Robust Point Matching using Learned Features
论文：https://arxiv.org/abs/2003.13479
代码：https://github.com/yewzijian/RPMNet

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

Cascaded Refinement Network for Point Cloud Completion
论文：https://arxiv.org/abs/2004.03327
代码：https://github.com/xiaogangw/cascaded-point-completion

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

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

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

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

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

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

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

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

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

文本识别OCR

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

Deep Relational Reasoning Graph Network for Arbitrary Shape Text Detection
论文：https://arxiv.org/abs/2003.07493
代码：https://github.com/GXYM/DRRG

UnrealText: Synthesizing Realistic Scene Text Images from the Unreal World
论文：https://arxiv.org/abs/2003.10608
代码：https://github.com/Jyouhou/UnrealText/

Learn to Augment: Joint Data Augmentation and Network Optimization for Text Recognition
论文：https://arxiv.org/abs/2003.06606
代码：https://github.com/Canjie-Luo/Text-Image-Augmentation

弱监督 & 无监督学习

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

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

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

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

迁移学习

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

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

图神经网络GNN

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

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

在公众号后台回复：CVPR2020，即可下载所有1470 篇论文，共2.5G

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