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ORCID17th ECCV 2022: Tel Aviv, Israel - Volume 24
- Shai Avidan, Gabriel J. Brostow
, Moustapha Cissé, Giovanni Maria Farinella, Tal Hassner:
Computer Vision - ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XXIV. Lecture Notes in Computer Science 13684, Springer 2022, ISBN 978-3-031-20053-3 - Jiawang Bai, Li Yuan, Shu-Tao Xia, Shuicheng Yan, Zhifeng Li, Wei Liu:
Improving Vision Transformers by Revisiting High-Frequency Components. 1-18 - Sheng Xu, Yanjing Li, Tiancheng Wang, Teli Ma, Baochang Zhang, Peng Gao, Yu Qiao, Jinhu Lü, Guodong Guo:
Recurrent Bilinear Optimization for Binary Neural Networks. 19-35 - Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Priyadarshini Panda:
Neural Architecture Search for Spiking Neural Networks. 36-56 - Yang Liu, Lei Zhou, Pengcheng Zhang, Xiao Bai, Lin Gu, Xiaohan Yu, Jun Zhou, Edwin R. Hancock:
Where to Focus: Investigating Hierarchical Attention Relationship for Fine-Grained Visual Classification. 57-73 - Mingyu Ding, Bin Xiao, Noel Codella, Ping Luo, Jingdong Wang, Lu Yuan:
DaViT: Dual Attention Vision Transformers. 74-92 - Jiangming Wang, Zhizhong Zhang, Mingang Chen, Yi Zhang, Cong Wang, Bin Sheng, Yanyun Qu, Yuan Xie:
Optimal Transport for Label-Efficient Visible-Infrared Person Re-Identification. 93-109 - Kehan Li, Runyi Yu, Zhennan Wang, Li Yuan, Guoli Song, Jie Chen:
Locality Guidance for Improving Vision Transformers on Tiny Datasets. 110-127 - Jichang Li, Guanbin Li, Feng Liu, Yizhou Yu:
Neighborhood Collective Estimation for Noisy Label Identification and Correction. 128-145 - Huan Liu, Li Gu, Zhixiang Chi, Yang Wang, Yuanhao Yu, Jun Chen, Jin Tang:
Few-Shot Class-Incremental Learning via Entropy-Regularized Data-Free Replay. 146-162 - Runqi Wang, Yuxiang Bao, Baochang Zhang, Jianzhuang Liu, Wentao Zhu, Guodong Guo:
Anti-retroactive Interference for Lifelong Learning. 163-178 - Hualiang Wang, Siming Fu, Xiaoxuan He, Hangxiang Fang, Zuozhu Liu, Haoji Hu:
Towards Calibrated Hyper-Sphere Representation via Distribution Overlap Coefficient for Long-Tailed Learning. 179-196 - Wenzhao Zheng, Yuan Huang, Borui Zhang, Jie Zhou, Jiwen Lu:
Dynamic Metric Learning with Cross-Level Concept Distillation. 197-213 - Linhui Sun, Yifan Zhang, Ke Cheng, Jian Cheng, Hanqing Lu:
MENet: A Memory-Based Network with Dual-Branch for Efficient Event Stream Processing. 214-234 - Sen Pei, Xin Zhang, Bin Fan, Gaofeng Meng:
Out-of-distribution Detection with Boundary Aware Learning. 235-251 - Ashima Garg, Depanshu Sani, Saket Anand:
Learning Hierarchy Aware Features for Reducing Mistake Severity. 252-267 - Kuniaki Saito, Ping Hu, Trevor Darrell, Kate Saenko:
Learning to Detect Every Thing in an Open World. 268-284 - Pichao Wang, Xue Wang, Fan Wang, Ming Lin, Shuning Chang, Hao Li, Rong Jin:
KVT: k-NN Attention for Boosting Vision Transformers. 285-302 - Chaoqin Huang, Haoyan Guan, Aofan Jiang, Ya Zhang, Michael W. Spratling, Yanfeng Wang:
Registration Based Few-Shot Anomaly Detection. 303-319 - Yong Guo, David Stutz, Bernt Schiele:
Improving Robustness by Enhancing Weak Subnets. 320-338 - Tian Zhang, Kongming Liang, Ruoyi Du, Xian Sun, Zhanyu Ma, Jun Guo:
Learning Invariant Visual Representations for Compositional Zero-Shot Learning. 339-355 - Yue Song, Nicu Sebe, Wei Wang:
Improving Covariance Conditioning of the SVD Meta-layer by Orthogonality. 356-372 - Yijun Yang, Ruiyuan Gao, Qiang Xu:
Out-of-Distribution Detection with Semantic Mismatch Under Masking. 373-390 - Zechun Liu, Zhiqiang Shen, Yun Long, Eric P. Xing, Kwang-Ting Cheng, Chas Leichner:
Data-Free Neural Architecture Search via Recursive Label Calibration. 391-406 - Zhengqi Gao, Fan-Keng Sun, Mingran Yang, Sucheng Ren, Zikai Xiong, Marc Engeler, Antonio Burazer, Linda Wildling, Luca Daniel, Duane S. Boning:
Learning from Multiple Annotator Noisy Labels via Sample-Wise Label Fusion. 407-422 - Donghao Zhou, Pengfei Chen, Qiong Wang, Guangyong Chen, Pheng-Ann Heng:
Acknowledging the Unknown for Multi-label Learning with Single Positive Labels. 423-440 - Zicheng Liu, Siyuan Li, Di Wu, Zihan Liu, Zhiyuan Chen, Lirong Wu, Stan Z. Li:
AutoMix: Unveiling the Power of Mixup for Stronger Classifiers. 441-458 - Zhengzhong Tu, Hossein Talebi, Han Zhang, Feng Yang, Peyman Milanfar, Alan C. Bovik, Yinxiao Li:
MaxViT: Multi-axis Vision Transformer. 459-479 - Rui Yang, Hailong Ma, Jie Wu, Yansong Tang, Xuefeng Xiao, Min Zheng, Xiu Li:
ScalableViT: Rethinking the Context-Oriented Generalization of Vision Transformer. 480-496 - Hugo Touvron, Matthieu Cord, Alaaeldin El-Nouby, Jakob Verbeek, Hervé Jégou:
Three Things Everyone Should Know About Vision Transformers. 497-515 - Hugo Touvron, Matthieu Cord, Hervé Jégou:
DeiT III: Revenge of the ViT. 516-533 - Chuanguang Yang, Zhulin An, Helong Zhou, Linhang Cai, Xiang Zhi, Jiwen Wu, Yongjun Xu, Qian Zhang:
MixSKD: Self-Knowledge Distillation from Mixup for Image Recognition. 534-551 - Zhou Yang, Weisheng Dong, Xin Li, Jinjian Wu, Leida Li, Guangming Shi:
Self-feature Distillation with Uncertainty Modeling for Degraded Image Recognition. 552-569 - K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian:
Novel Class Discovery Without Forgetting. 570-586 - Yan Hong, Jianfu Zhang, Zhongyi Sun, Ke Yan:
SAFA: Sample-Adaptive Feature Augmentation for Long-Tailed Image Classification. 587-603 - Hyungtae Lee, Sungmin Eum, Heesung Kwon:
Negative Samples are at Large: Leveraging Hard-Distance Elastic Loss for Re-identification. 604-620 - Haipeng Xiong, Angela Yao:
Discrete-Constrained Regression for Local Counting Models. 621-636 - Bo Liu, Haoxiang Li, Hao Kang, Gang Hua, Nuno Vasconcelos:
Breadcrumbs: Adversarial Class-Balanced Sampling for Long-Tailed Recognition. 637-653 - Guangzhi Wang, Yangyang Guo, Yongkang Wong, Mohan S. Kankanhalli:
Chairs Can Be Stood On: Overcoming Object Bias in Human-Object Interaction Detection. 654-672 - Zhiqiang Shen, Eric P. Xing:
A Fast Knowledge Distillation Framework for Visual Recognition. 673-690 - Yiyou Sun, Yixuan Li:
DICE: Leveraging Sparsification for Out-of-Distribution Detection. 691-708 - Kaihua Tang, Mingyuan Tao, Jiaxin Qi, Zhenguang Liu, Hanwang Zhang:
Invariant Feature Learning for Generalized Long-Tailed Classification. 709-726 - Zhiqiang Shen, Zechun Liu, Eric P. Xing:
Sliced Recursive Transformer. 727-744
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