关键词：
CVPR是IEEE Conference on Computer Vision and Pattern Recognition的缩写，即IEEE国际计算机视觉与模式识别会议。该会议是由IEEE举办的计算机视觉和模式识别领域的顶级会议。
国际计算机视觉与模式识别会议（CVPR）是IEEE一年一度的学术性会议，会议的主要内容是计算机视觉与模式识别技术。CVPR是世界顶级的计算机视觉会议（三大顶会之一，另外两个是ICCV和ECCV）
CVPR2022还没有开始，我们先回顾CVPR2021
我自己总结持续更新Github上面：https://github.com/Sophia-11/Awesome-CVPR-Paper
CVPR2021最新更新论文
Image-to-image Translation via Hierarchical Style Disentanglement Xinyang Li, Shengchuan Zhang, Jie Hu, Liujuan Cao, Xiaopeng Hong, Xudong Mao, Feiyue Huang, Yongjian Wu, Rongrong Ji https://arxiv.org/abs/2103.01456 https://github.com/imlixinyang/HiSD
FLAVR: Flow-Agnostic Video Representations for Fast Frame Interpolation https://arxiv.org/pdf/2012.08512.pdf https://tarun005.github.io/FLAVR/Code https://tarun005.github.io/FLAVR/
Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition Stephen Hausler, Sourav Garg, Ming Xu, Michael Milford, Tobias Fischer https://arxiv.org/abs/2103.01486
Depth from Camera Motion and Object Detection Brent A. Griffin, Jason J. Corso https://arxiv.org/abs/2103.01468
UP-DETR: Unsupervised Pre-training for Object Detection with Transformers https://arxiv.org/pdf/2011.09094.pdf
Multi-Stage Progressive Image Restoration https://arxiv.org/abs/2102.02808 https://github.com/swz30/MPRNet
Weakly Supervised Learning of Rigid 3D Scene Flow https://arxiv.org/pdf/2102.08945.pdf https://arxiv.org/pdf/2102.08945.pdf https://3dsceneflow.github.io/
Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning Mamshad Nayeem Rizve, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah https://arxiv.org/abs/2103.01315
Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels https://arxiv.org/abs/2101.05022 https://github.com/naver-ai/relabel_imagenet
Rethinking Channel Dimensions for Efficient Model Design https://arxiv.org/abs/2007.00992 https://github.com/clovaai/rexnet
Coarse-Fine Networks for Temporal Activity Detection in Videos Kumara Kahatapitiya, Michael S. Ryoo https://arxiv.org/abs/2103.01302
A Deep Emulator for Secondary Motion of 3D Characters Mianlun Zheng, Yi Zhou, Duygu Ceylan, Jernej Barbic https://arxiv.org/abs/2103.01261
Fair Attribute Classification through Latent Space De-biasing https://arxiv.org/abs/2012.01469 https://github.com/princetonvisualai/gan-debiasing https://princetonvisualai.github.io/gan-debiasing/
Auto-Exposure Fusion for Single-Image Shadow Removal Lan Fu, Changqing Zhou, Qing Guo, Felix Juefei-Xu, Hongkai Yu, Wei Feng, Yang Liu, Song Wang https://arxiv.org/abs/2103.01255
Less is More: CLIPBERT for Video-and-Language Learning via Sparse Sampling https://arxiv.org/pdf/2102.06183.pdf https://github.com/jayleicn/ClipBERT
MetaSCI: Scalable and Adaptive Reconstruction for Video Compressive Sensing Zhengjue Wang, Hao Zhang, Ziheng Cheng, Bo Chen, Xin Yuan https://arxiv.org/abs/2103.01786
AttentiveNAS: Improving Neural Architecture Search via Attentive https://arxiv.org/pdf/2011.09011.pdf
Diffusion Probabilistic Models for 3D Point Cloud Generation Shitong Luo, Wei Hu https://arxiv.org/abs/2103.01458
There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge Francisco Rivera Valverde, Juana Valeria Hurtado, Abhinav Valada https://arxiv.org/abs/2103.01353 http://rl.uni-freiburg.de/research/multimodal-distill
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation https://arxiv.org/abs/2008.00951 https://github.com/eladrich/pixel2style2pixel https://eladrich.github.io/pixel2style2pixel/
Hierarchical and Partially Observable Goal-driven Policy Learning with Goals Relational Graph Xin Ye, Yezhou Yang https://arxiv.org/abs/2103.01350
RepVGG: Making VGG-style ConvNets Great Again https://arxiv.org/abs/2101.03697 https://github.com/megvii-model/RepVGG
Transformer Interpretability Beyond Attention Visualization https://arxiv.org/pdf/2012.09838.pdf https://github.com/hila-chefer/Transformer-Explainability
PREDATOR: Registration of 3D Point Clouds with Low Overlap https://arxiv.org/pdf/2011.13005.pdf https://github.com/ShengyuH/OverlapPredator https://overlappredator.github.io/
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