2022 CVPR에서 서울대학교 논문이 25편 채택되었다. 공과대학에서는 전기정보공학부 이정우 교수팀, 문태섭 교수팀, 조남익 교수팀에서 각 1편, 한보형 교수팀 5편, 이경무 교수팀 5편, 윤성로 교수팀 6편이 채택되었으며, 컴퓨터공학부 장병탁 교수팀 1편, 조한별 교수팀 3편이 채택 되었다. 융합과학기술대학원에서는 곽노준 교수팀에서 3편이 채택되었다. 

2022 CVPR 채택 논문 

• Large Loss Matters in Weakly Supervised Multi-Label Classification (Youngwook Kim*, Jae Myung Kim*, Zeynep Akata, and Jungwoo Lee) #이정우 교수팀
• Learning Fair Classifiers with Partially Annotated Group Labels (Sangwon Jung, Sanghyuk Chun, and Taesup Moon) #문태섭 교수팀
  
• LC-FDNet: Learned Lossless Image Compression with Frequency Decomposition Network (Hochang Rhee, Yeong Il Jang, Seyun Kim, Nam Ik Cho) #조남익 교수팀
  
• Self-Supervised Dense Consistency Regularization for Image-to-Image Translation (Minsu Ko*, Eunju Cha*, Sungjoo Suh, Huijin Lee, Jae-Joon Han, Jinwoo Shin, and Bohyung Han) #한보형 교수팀
  
• InfoNeRF: Ray Entropy Minimization for Few-Shot Neural Volume Rendering (Mijeong Kim, Seonguk Seo, and Bohyung Han) #한보형 교수팀
  
• Unsupervised Learning of Debiased Representations with Pseudo-Attributes (Seonguk Seo, Joon-Young Lee, and Bohyung Han) #한보형 교수팀
  
• Class-Incremental Learning by Knowledge Distillation with Adaptive Feature Consolidation (Minsoo Kang, Jaeyoo Park, and Bohyung Han) #한보형 교수팀
  
• Pooling Revisited: Your Receptive Field is Sub-optimal (Dong-Hwan Jang, Sanghyeok Chu, Joonhyuk Kim, and Bohyung Han) #한보형 교수팀
  
• CVF-SID: Cyclic multi-Variate Function for Self-Supervised Image Denoising by Disentangling Noise from Image (Reyhaneh Neshatavar*, Mohsen Yavartanoo*, Sanghyun Son, and Kyoung Mu Lee) #이경무 교수팀
  
• HandOccNet: Occlusion-Robust 3D Hand Mesh Estimation Network (Joonkyu Park*, Yeonguk Oh*, Gyeongsik Moon*, Hongsuk Choi, and Kyoung Mu Lee) #이경무 교수팀
  
• AP-BSN: Self-Supervised Denoising for Real-World Images via Asymmetric PD and Blind-Spot Network (Wooseok Lee, Sanghyun Son, and Kyoung Mu Lee) #이경무 교수팀
  
• Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenes (Hongsuk Choi, Gyeongsik Moon, JoonKyu Park, and Kyoung Mu Lee) #이경무 교수팀
  
• Attentive Fine-Grained Structured Sparsity for Image Restoration (Junghun Oh, Heewon Kim, Seungjun Nah, Cheeun Hong, Jonghyun Choi, and Kyoung Mu Lee) #이경무 교수팀
  
• Demystifying the Neural Tangent Kernel from a Practical Perspective: Can it be trusted for Neural Architecture Search without training? (Jisoo Mok, Byunggook Na, Ji-Hoon Kim, Dongyoon Han, Sungroh Yoon) #윤성로 교수팀
• Weakly Supervised Semantic Segmentation using Out-of-Distribution Data (Jungbeom Lee, Seong Joon Oh, Sangdoo Yun, Junsuk Choe, Eunji Kim, Sungroh Yoon) #윤성로 교수팀
• Bridging the Gap between Classification and Localization by Aligning Feature Directions for Weakly Supervised Object Localization (Eunji Kim, Siwon Kim, Jungbeom Lee, Hyunwoo Kim, Sungroh Yoon) #윤성로 교수팀
  
• Perception Prioritized Training of Diffusion Models (Jooyoung Choi, Jungbeom Lee, Chaehun Shin, Sungwon Kim, Hyunwoo Kim, Sungroh Yoon) #윤성로 교수팀
  
• BNUDC: A Two-Branched Deep Neural Network for Restoring Images from Under-Display Cameras (Jaihyun Koh, Jangho Lee, Sungroh Yoon) #윤성로 교수팀
• Smooth-Swap: A Simple Enhancement for Face-Swapping with Smoothness (Jiseob Kim, Jihoon Lee, Byoung-Tak Zhang) #장병탁 교수팀
  
• Learning to Listen: Modeling Non-Deterministic Dyadic Facial Motion (Evonne Ng , Hanbyul Joo, Liwen Hu, Hao Li, Trevor Darrell, Angjoo Kanazawa, Shiry Ginosar) #주한별 교수팀
  
• BANMo: Building Animatable 3D Neural Models from Many Casual Videos (Gengshan Yang, Minh Vo, Natalia Neverova, Deva Ramanan, Andrea Vedaldi, Hanbyul Joo) #주한별 교수팀
  
• Ego4D: Around the World in 3,000 Hours of Egocentric Video (Kristen Grauman et al. ) #주한별 교수팀
• MUM : Mix Image Tiles and UnMix Feature Tiles for Semi-Supervised Object Detection (JongMok Kim, Jooyoung Jang, Seunghyeon Seo, Jisoo Jeong, Jongkeun Na, Nojun Kwak) #곽노준 교수팀
  
• MatteFormer: Transformer-Based Image Matting via Prior-Tokens (GyuTae Park, Sungjoon Son, Jaeyoung Yoo, Seho Kim, Nojun Kwak) #곽노준 교수팀
  
• Imposing Consistency for Optical Flow Estimation (Jisoo Jeong, Jamie Menjay Lin, Fatih Porikli, Nojun Kwak) #곽노준 교수팀