【CVPR 2021 论文开源目录】
https://github.com/amusi/CVPR2021-Papers-with-Code
- Backbone
- NAS
- GAN
- Visual Transformer
- 自监督(Self-Supervised)
- 目标检测(Object Detection)
- 实例分割(Instance Segmentation)
- 全景分割(Panoptic Segmentation)
- 视频理解/行为识别(Video Understanding)
- 人脸识别(Face Recognition)
- 人脸活体检测(Face Anti-Spoofing)
- Deepfake检测(Deepfake Detection)
- 人脸年龄估计(Age-Estimation)
- 人脸解析(Human Parsing)
- 超分辨率(Super-Resolution)
- 图像恢复(Image Restoration)
- 3D目标检测(3D Object Detection)
- 3D语义分割(3D Semantic Segmentation)
- 3D目标跟踪(3D Object Tracking)
- 3D点云配准(3D Point Cloud Registration)
- 6D位姿估计(6D Pose Estimation)
- 深度估计(Depth Estimation)
- 对抗样本(Adversarial-Examples)
- 图像检索(Image Retrieval)
- Zero-Shot Learning
- 视觉推理(Visual Reasoning)
- "人-物"交互(HOI)检测
- 阴影去除(Shadow Removal)
- 数据集(Datasets)
- 其他(Others)
- 不确定中没中(Not Sure)
Coordinate Attention for Efficient Mobile Network Design
- Paper: https://arxiv.org/abs/2103.02907
- Code: https://github.com/Andrew-Qibin/CoordAttention
Inception Convolution with Efficient Dilation Search
- Paper: https://arxiv.org/abs/2012.13587
- Code: None
RepVGG: Making VGG-style ConvNets Great Again
- Paper: https://arxiv.org/abs/2101.03697
- Code: https://github.com/DingXiaoH/RepVGG
Inception Convolution with Efficient Dilation Search
- Paper: https://arxiv.org/abs/2012.13587
- Code: None
Training Generative Adversarial Networks in One Stage
- Paper: https://arxiv.org/abs/2103.00430
- Code: None
Closed-Form Factorization of Latent Semantics in GANs
- Homepage: https://genforce.github.io/sefa/
- Paper: https://arxiv.org/abs/2007.06600
- Code: https://github.com/genforce/sefa
Anycost GANs for Interactive Image Synthesis and Editing
- Paper: https://arxiv.org/abs/2103.03243
- Code: https://github.com/mit-han-lab/anycost-gan
Image-to-image Translation via Hierarchical Style Disentanglement
- Paper: https://arxiv.org/abs/2103.01456
- Code: https://github.com/imlixinyang/HiSD
End-to-End Video Instance Segmentation with Transformers
- Paper(Oral): https://arxiv.org/abs/2011.14503
- Code: None
UP-DETR: Unsupervised Pre-training for Object Detection with Transformers
- Paper(Oral): https://arxiv.org/abs/2011.09094
- Code: https://github.com/dddzg/up-detr
End-to-End Human Object Interaction Detection with HOI Transformer
- Paper: https://arxiv.org/abs/2103.04503
- Code: https://github.com/bbepoch/HoiTransformer
Transformer Interpretability Beyond Attention Visualization
- Paper: https://arxiv.org/abs/2012.09838
- Code: https://github.com/hila-chefer/Transformer-Explainability
Dense Contrastive Learning for Self-Supervised Visual Pre-Training
- Paper: https://arxiv.org/abs/2011.09157
- Code: https://github.com/WXinlong/DenseCL
UP-DETR: Unsupervised Pre-training for Object Detection with Transformers
- Paper(Oral): https://arxiv.org/abs/2011.09094
- Code: https://github.com/dddzg/up-detr
General Instance Distillation for Object Detection
- Paper: https://arxiv.org/abs/2103.02340
- Code: None
Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection
- Paper: https://arxiv.org/abs/2103.01903
- Code: None
There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge
- Homepage: http://rl.uni-freiburg.de/research/multimodal-distill
- Paper: https://arxiv.org/abs/2103.01353
- Code: http://rl.uni-freiburg.de/research/multimodal-distill
Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection
- Paper: https://arxiv.org/abs/2011.12885
- Code: https://github.com/implus/GFocalV2
Multiple Instance Active Learning for Object Detection
- Paper: https://github.com/yuantn/MIAL/raw/master/paper.pdf
- Code: https://github.com/yuantn/MIAL
Towards Open World Object Detection
- Paper: https://arxiv.org/abs/2103.02603
- Code: https://github.com/JosephKJ/OWOD
End-to-End Video Instance Segmentation with Transformers
- Paper(Oral): https://arxiv.org/abs/2011.14503
- Code: None
Zero-shot instance segmentation(Not Sure)
- Paper: None
- Code: https://github.com/CVPR2021-pape-id-1395/CVPR2021-paper-id-1395
Cross-View Regularization for Domain Adaptive Panoptic Segmentation
- Paper: https://arxiv.org/abs/2103.02584
- Code: None
TDN: Temporal Difference Networks for Efficient Action Recognition
- Paper: https://arxiv.org/abs/2012.10071
- Code: https://github.com/MCG-NJU/TDN
WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition
- Homepage: https://www.face-benchmark.org/
- Paper: https://arxiv.org/abs/2103.04098
- Dataset: https://www.face-benchmark.org/
When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework
- Paper(Oral): https://arxiv.org/abs/2103.01520
- Code: https://github.com/Hzzone/MTLFace
- Dataset: https://github.com/Hzzone/MTLFace
Cross Modal Focal Loss for RGBD Face Anti-Spoofing
- Paper: https://arxiv.org/abs/2103.00948
- Code: None
Spatial-Phase Shallow Learning: Rethinking Face Forgery Detection in Frequency Domain
- Paper:https://arxiv.org/abs/2103.01856
- Code: None
Multi-attentional Deepfake Detection
- Paper:https://arxiv.org/abs/2103.02406
- Code: None
PML: Progressive Margin Loss for Long-tailed Age Classification
- Paper: https://arxiv.org/abs/2103.02140
- Code: None
Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsing
- Paper: https://arxiv.org/abs/2103.04570
- Code: https://github.com/tfzhou/MG-HumanParsing
ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic
- Paper: https://arxiv.org/abs/2103.04039
- Code: https://github.com/Xiangtaokong/ClassSR
AdderSR: Towards Energy Efficient Image Super-Resolution
- Paper: https://arxiv.org/abs/2009.08891
- Code: None
Multi-Stage Progressive Image Restoration
- Paper: https://arxiv.org/abs/2102.02808
- Code: https://github.com/swz30/MPRNet
SE-SSD: Self-Ensembling Single-Stage Object Detector From Point Cloud
- Paper: None
- Code: https://github.com/Vegeta2020/SE-SSD
Center-based 3D Object Detection and Tracking
- Paper: https://arxiv.org/abs/2006.11275
- Code: https://github.com/tianweiy/CenterPoint
Categorical Depth Distribution Network for Monocular 3D Object Detection
- Paper: https://arxiv.org/abs/2103.01100
- Code: None
Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges
- Homepage: https://github.com/QingyongHu/SensatUrban
- Paper: http://arxiv.org/abs/2009.03137
- Code: https://github.com/QingyongHu/SensatUrban
- Dataset: https://github.com/QingyongHu/SensatUrban
Center-based 3D Object Detection and Tracking
- Paper: https://arxiv.org/abs/2006.11275
- Code: https://github.com/tianweiy/CenterPoint
PREDATOR: Registration of 3D Point Clouds with Low Overlap
- Paper: https://arxiv.org/abs/2011.13005
- Code: https://github.com/ShengyuH/OverlapPredator
FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation
- Paper: https://arxiv.org/abs/2103.02242
- Code: https://github.com/ethnhe/FFB6D
Depth from Camera Motion and Object Detection
- Paper: https://arxiv.org/abs/2103.01468
- Code: https://github.com/griffbr/ODMD
- Dataset: https://github.com/griffbr/ODMD
Natural Adversarial Examples
- Paper: https://arxiv.org/abs/1907.07174
- Code: https://github.com/hendrycks/natural-adv-examples
QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval
- Paper: https://arxiv.org/abs/2103.02927
- Code: None
Counterfactual Zero-Shot and Open-Set Visual Recognition
- Paper: https://arxiv.org/abs/2103.00887
- Code: https://github.com/yue-zhongqi/gcm-cf
Transformation Driven Visual Reasoning
- homepage: https://hongxin2019.github.io/TVR/
- Paper: https://arxiv.org/abs/2011.13160
- Code: https://github.com/hughplay/TVR
End-to-End Human Object Interaction Detection with HOI Transformer
- Paper: https://arxiv.org/abs/2103.04503
- Code: https://github.com/bbepoch/HoiTransformer
Auto-Exposure Fusion for Single-Image Shadow Removal
- Paper: https://arxiv.org/abs/2103.01255
- Code: https://github.com/tsingqguo/exposure-fusion-shadow-removal
Nutrition5k: Towards Automatic Nutritional Understanding of Generic Food
- Paper: https://arxiv.org/abs/2103.03375
- Dataset: None
Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges
- Homepage: https://github.com/QingyongHu/SensatUrban
- Paper: http://arxiv.org/abs/2009.03137
- Code: https://github.com/QingyongHu/SensatUrban
- Dataset: https://github.com/QingyongHu/SensatUrban
When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework
- Paper(Oral): https://arxiv.org/abs/2103.01520
- Code: https://github.com/Hzzone/MTLFace
- Dataset: https://github.com/Hzzone/MTLFace
Depth from Camera Motion and Object Detection
- Paper: https://arxiv.org/abs/2103.01468
- Code: https://github.com/griffbr/ODMD
- Dataset: https://github.com/griffbr/ODMD
There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge
- Homepage: http://rl.uni-freiburg.de/research/multimodal-distill
- Paper: https://arxiv.org/abs/2103.01353
- Code: http://rl.uni-freiburg.de/research/multimodal-distill
Scan2Cap: Context-aware Dense Captioning in RGB-D Scans
- Paper: https://arxiv.org/abs/2012.02206
- Code: https://github.com/daveredrum/Scan2Cap
- Dataset: https://github.com/daveredrum/ScanRefer
There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge
- Paper: https://arxiv.org/abs/2103.01353
- Code: http://rl.uni-freiburg.de/research/multimodal-distill
- Dataset: http://rl.uni-freiburg.de/research/multimodal-distill
Knowledge Evolution in Neural Networks
- Paper(Oral): https://arxiv.org/abs/2103.05152
- Code: https://github.com/ahmdtaha/knowledge_evolution
Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning
- Paper: https://arxiv.org/abs/2103.02148
- Code: https://github.com/guopengf/FLMRCM
SGP: Self-supervised Geometric Perception
- Oral
- Paper: https://arxiv.org/abs/2103.03114
- Code: https://github.com/theNded/SGP
Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning
- Paper: https://arxiv.org/abs/2103.02148
- Code: https://github.com/guopengf/FLMRCM
Diffusion Probabilistic Models for 3D Point Cloud Generation
- Paper: https://arxiv.org/abs/2103.01458
- Code: https://github.com/luost26/diffusion-point-cloud
Scan2Cap: Context-aware Dense Captioning in RGB-D Scans
- Paper: https://arxiv.org/abs/2012.02206
- Code: https://github.com/daveredrum/Scan2Cap
- Dataset: https://github.com/daveredrum/ScanRefer
There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge
- Paper: https://arxiv.org/abs/2103.01353
- Code: http://rl.uni-freiburg.de/research/multimodal-distill
- Dataset: http://rl.uni-freiburg.de/research/multimodal-distill
CT Film Recovery via Disentangling Geometric Deformation and Photometric Degradation: Simulated Datasets and Deep Models
- Paper: none
- Code: https://github.com/transcendentsky/Film-Recovery
Toward Explainable Reflection Removal with Distilling and Model Uncertainty
- Paper: none
- Code: https://github.com/ytpeng-aimlab/CVPR-2021-Toward-Explainable-Reflection-Removal-with-Distilling-and-Model-Uncertainty
DeepOIS: Gyroscope-Guided Deep Optical Image Stabilizer Compensation
- Paper: none
- Code: https://github.com/lhaippp/DeepOIS
Exploring Adversarial Fake Images on Face Manifold
- Paper: none
- Code: https://github.com/ldz666666/Style-atk
Uncertainty-Aware Semi-Supervised Crowd Counting via Consistency-Regularized Surrogate Task
- Paper: none
- Code: https://github.com/yandamengdanai/Uncertainty-Aware-Semi-Supervised-Crowd-Counting-via-Consistency-Regularized-Surrogate-Task
Temporal Contrastive Graph for Self-supervised Video Representation Learning
- Paper: none
- Code: https://github.com/YangLiu9208/TCG
Boosting Monocular Depth Estimation Models to High-Resolution via Context-Aware Patching
- Paper: none
- Code: https://github.com/ouranonymouscvpr/cvpr2021_ouranonymouscvpr
Fast and Memory-Efficient Compact Bilinear Pooling
- Paper: none
- Code: https://github.com/cvpr2021kp2/cvpr2021kp2
Identification of Empty Shelves in Supermarkets using Domain-inspired Features with Structural Support Vector Machine
- Paper: none
- Code: https://github.com/gapDetection/cvpr2021
Estimating A Child's Growth Potential From Cephalometric X-Ray Image via Morphology-Aware Interactive Keypoint Estimation
- Paper: none
- Code: https://github.com/interactivekeypoint2020/Morph
https://github.com/ShaoQiangShen/CVPR2021
https://github.com/gillesflash/CVPR2021
https://github.com/anonymous-submission1991/BaLeNAS
https://github.com/cvpr2021dcb/cvpr2021dcb
https://github.com/anonymousauthorCV/CVPR2021_PaperID_8578
https://github.com/AldrichZeng/FreqPrune
https://github.com/Anonymous-AdvCAM/Anonymous-AdvCAM
https://github.com/ddfss/datadrive-fss
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