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ORCID17th ECCV 2022: Tel Aviv, Israel - Volume 25
- 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 XXV. Lecture Notes in Computer Science 13685, Springer 2022, ISBN 978-3-031-19805-2 - Kyungmoon Lee, Sungyeon Kim, Suha Kwak:
Cross-domain Ensemble Distillation for Domain Generalization. 1-20 - Ganlong Zhao, Guanbin Li, Yipeng Qin, Feng Liu, Yizhou Yu:
Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels. 21-37 - Bo Ke, Yunquan Zhu, Mengtian Li, Xiujun Shu, Ruizhi Qiao, Bo Ren:
Hyperspherical Learning in Multi-Label Classification. 38-55 - Zhuangzhuang Chen, Jin Zhang, Pan Wang, Jie Chen, Jianqiang Li:
When Active Learning Meets Implicit Semantic Data Augmentation. 56-72 - Changyao Tian, Wenhai Wang, Xizhou Zhu, Jifeng Dai, Yu Qiao:
VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition. 73-91 - Jiaxin Qi, Kaihua Tang, Qianru Sun, Xian-Sheng Hua, Hanwang Zhang:
Class Is Invariant to Context and Vice Versa: On Learning Invariance for Out-Of-Distribution Generalization. 92-109 - Gaoang Wang, Yibing Zhan, Xinchao Wang, Mingli Song, Klara Nahrstedt:
Hierarchical Semi-supervised Contrastive Learning for Contamination-Resistant Anomaly Detection. 110-128 - Sanghyun Woo, Kwanyong Park, Seoung Wug Oh, In So Kweon, Joon-Young Lee:
Tracking by Associating Clips. 129-145 - Sara Romiti, Christopher Inskip, Viktoriia Sharmanska, Novi Quadrianto:
RealPatch: A Statistical Matching Framework for Model Patching with Real Samples. 146-162 - Liang Zhao, Zhenyao Wu, Xinyi Wu, Greg Wilsbacher, Song Wang:
Background-Insensitive Scene Text Recognition with Text Semantic Segmentation. 163-182 - Francesco Cappio Borlino, Silvia Bucci, Tatiana Tommasi:
Semantic Novelty Detection via Relational Reasoning. 183-200 - Khoi Pham, Kushal Kafle, Zhe Lin, Zhihong Ding, Scott Cohen, Quan Tran, Abhinav Shrivastava:
Improving Closed and Open-Vocabulary Attribute Prediction Using Transformers. 201-219 - Yun-Hao Cao, Hao Yu, Jianxin Wu:
Training Vision Transformers with only 2040 Images. 220-237 - Sanghyun Woo, Kwanyong Park, Seoung Wug Oh, In So Kweon, Joon-Young Lee:
Bridging Images and Videos: A Simple Learning Framework for Large Vocabulary Video Object Detection. 238-258 - Shantanu Jaiswal, Basura Fernando, Cheston Tan:
TDAM: Top-Down Attention Module for Contextually Guided Feature Selection in CNNs. 259-276 - Hao Chen, Xiu-Shen Wei, Faen Zhang, Yang Shen, Hui Xu, Liang Xiao:
Automatic Check-Out via Prototype-Based Classifier Learning from Single-Product Exemplars. 277-293 - Piyapat Saranrittichai, Chaithanya Kumar Mummadi, Claudia Blaiotta, Mauricio Munoz, Volker Fischer:
Overcoming Shortcut Learning in a Target Domain by Generalizing Basic Visual Factors from a Source Domain. 294-309 - Sergey Zakharov, Rares Ambrus, Vitor Guizilini, Wadim Kehl, Adrien Gaidon:
Photo-realistic Neural Domain Randomization. 310-327 - Ting Yao, Yingwei Pan, Yehao Li, Chong-Wah Ngo, Tao Mei:
Wave-ViT: Unifying Wavelet and Transformers for Visual Representation Learning. 328-345 - WonJun Moon, Ji-Hwan Kim, Jae-Pil Heo:
Tailoring Self-Supervision for Supervised Learning. 346-364 - WonJun Moon, Jun Ho Park, Hyun Seok Seong, Cheol-Ho Cho, Jae-Pil Heo:
Difficulty-Aware Simulator for Open Set Recognition. 365-381 - Can Peng, Kun Zhao, Tianren Wang, Meng Li, Brian C. Lovell:
Few-Shot Class-Incremental Learning from an Open-Set Perspective. 382-397 - Fu-Yun Wang, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan:
FOSTER: Feature Boosting and Compression for Class-Incremental Learning. 398-414 - Neehar Kondapaneni, Pietro Perona, Oisin Mac Aodha:
Visual Knowledge Tracing. 415-431 - Jayateja Kalla, Soma Biswas:
S3C: Self-Supervised Stochastic Classifiers for Few-Shot Class-Incremental Learning. 432-448 - Yangyang Shu, Baosheng Yu, Haiming Xu, Lingqiao Liu:
Improving Fine-Grained Visual Recognition in Low Data Regimes via Self-boosting Attention Mechanism. 449-465 - Qiming Zhang, Yufei Xu, Jing Zhang, Dacheng Tao:
VSA: Learning Varied-Size Window Attention in Vision Transformers. 466-483 - Baoming Yan, Ke Gao, Bo Gao, Lin Wang, Jiang Yang, Xiaobo Li:
Unbiased Manifold Augmentation for Coarse Class Subdivision. 484-499 - Matej Grcic, Petra Bevandic, Sinisa Segvic:
DenseHybrid: Hybrid Anomaly Detection for Dense Open-Set Recognition. 500-517 - Fei Zhu, Zhen Cheng, Xu-Yao Zhang, Cheng-Lin Liu:
Rethinking Confidence Calibration for Failure Prediction. 518-536 - Subhankar Roy, Martin Trapp, Andrea Pilzer, Juho Kannala, Nicu Sebe, Elisa Ricci, Arno Solin:
Uncertainty-Guided Source-Free Domain Adaptation. 537-555 - Yunsheng Li, Yinpeng Chen, Xiyang Dai, Dongdong Chen, Mengchen Liu, Pei Yu, Ying Jin, Lu Yuan, Zicheng Liu, Nuno Vasconcelos:
Should All Proposals Be Treated Equally in Object Detection? 556-572 - Junbo Li, Huan Zhang, Cihang Xie:
ViP: Unified Certified Detection and Recovery for Patch Attack with Vision Transformers. 573-587 - Amanda Rios, Nilesh A. Ahuja, Ibrahima J. Ndiour, Ergin Utku Genc, Laurent Itti, Omesh Tickoo:
incDFM: Incremental Deep Feature Modeling for Continual Novelty Detection. 588-604 - Yunsheng Pang, Qiuhong Ke, Hossein Rahmani, James Bailey, Jun Liu:
IGFormer: Interaction Graph Transformer for Skeleton-Based Human Interaction Recognition. 605-622 - Apostolos Modas, Rahul Rade, Guillermo Ortiz-Jiménez, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard:
PRIME: A Few Primitives Can Boost Robustness to Common Corruptions. 623-640 - Takumi Kobayashi:
Rotation Regularization Without Rotation. 641-657 - Wonwoo Cho, Jaegul Choo:
Towards Accurate Open-Set Recognition via Background-Class Regularization. 658-674 - Xianhang Li, Huiyu Wang, Chen Wei, Jieru Mei, Alan L. Yuille, Yuyin Zhou, Cihang Xie:
In Defense of Image Pre-Training for Spatiotemporal Recognition. 675-691 - Grigorios G. Chrysos, Markos Georgopoulos, Jiankang Deng, Jean Kossaifi, Yannis Panagakis, Anima Anandkumar:
Augmenting Deep Classifiers with Polynomial Neural Networks. 692-716 - Seong Min Kye, Kwanghee Choi, Joonyoung Yi, Buru Chang:
Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection. 717-738 - Julien Pourcel, Ngoc-Son Vu, Robert M. French:
Online Task-free Continual Learning with Dynamic Sparse Distributed Memory. 739-756
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