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ORCID17th ECCV 2022: Tel Aviv, Israel - Volume 11
- 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 XI. Lecture Notes in Computer Science 13671, Springer 2022, ISBN 978-3-031-20082-3 - Yutong Lin, Chen Li, Yue Cao, Zheng Zhang, Jianfeng Wang, Lijuan Wang, Zicheng Liu, Han Hu:
A Simple Approach and Benchmark for 21, 000-Category Object Detection. 1-18 - Chenxin Li, Mingbao Lin, Zhiyuan Ding, Nie Lin, Yihong Zhuang, Yue Huang, Xinghao Ding, Liujuan Cao:
Knowledge Condensation Distillation. 19-35 - Yufei Guo, Yuanpei Chen, Liwen Zhang, YingLei Wang, Xiaode Liu, Xinyi Tong, Yuanyuan Ou, Xuhui Huang, Zhe Ma:
Reducing Information Loss for Spiking Neural Networks. 36-52 - Zhendong Yang, Zhe Li, Mingqi Shao, Dachuan Shi, Zehuan Yuan, Chun Yuan:
Masked Generative Distillation. 53-69 - Yunshan Zhong, Mingbao Lin, Mengzhao Chen, Ke Li, Yunhang Shen, Fei Chao, Yongjian Wu, Rongrong Ji:
Fine-grained Data Distribution Alignment for Post-Training Quantization. 70-86 - Jingwen Ye, Yifang Fu, Jie Song, Xingyi Yang, Songhua Liu, Xin Jin, Mingli Song, Xinchao Wang:
Learning with Recoverable Forgetting. 87-103 - Jiajun Liang, Linze Li, Zhaodong Bing, Borui Zhao, Yao Tang, Bo Lin, Haoqiang Fan:
Efficient One Pass Self-distillation with Zipf's Label Smoothing. 104-119 - Jinhyuk Park, Albert No:
Prune Your Model Before Distill It. 120-136 - Zhongnan Qu, Cong Liu, Lothar Thiele:
Deep Partial Updating: Towards Communication Efficient Updating for On-Device Inference. 137-153 - Zhikai Li, Liping Ma, Mengjuan Chen, Junrui Xiao, Qingyi Gu:
Patch Similarity Aware Data-Free Quantization for Vision Transformers. 154-170 - Jonghyun Bae, Woohyeon Baek, Tae Jun Ham, Jae W. Lee:
L3: Accelerator-Friendly Lossless Image Format for High-Resolution, High-Throughput DNN Training. 171-188 - Can Ufuk Ertenli, Emre Akbas, Ramazan Gokberk Cinbis:
Streaming Multiscale Deep Equilibrium Models. 189-205 - Sein Park, Yeongsang Jang, Eunhyeok Park:
Symmetry Regularization and Saturating Nonlinearity for Robust Quantization. 206-222 - Huanyu Wang, Wenhu Zhang, Shihao Su, Hui Wang, Zhenwei Miao, Xin Zhan, Xi Li:
SP-Net: Slowly Progressing Dynamic Inference Networks. 223-240 - Tan Wang, Qianru Sun, Sugiri Pranata, Jayashree Karlekar, Hanwang Zhang:
Equivariance and Invariance Inductive Bias for Learning from Insufficient Data. 241-258 - Chen Tang, Kai Ouyang, Zhi Wang, Yifei Zhu, Wen Ji, Yaowei Wang, Wenwu Zhu:
Mixed-Precision Neural Network Quantization via Learned Layer-Wise Importance. 259-275 - Matthew Dutson, Yin Li, Mohit Gupta:
Event Neural Networks. 276-293 - Junting Pan, Adrian Bulat, Fuwen Tan, Xiatian Zhu, Lukasz Dudziak, Hongsheng Li, Georgios Tzimiropoulos, Brais Martínez:
EdgeViTs: Competing Light-Weight CNNs on Mobile Devices with Vision Transformers. 294-311 - Qinghao Hu, Gang Li, Qiman Wu, Jian Cheng:
PalQuant: Accelerating High-Precision Networks on Low-Precision Accelerators. 312-327 - Shangqian Gao, Feihu Huang, Yanfu Zhang, Heng Huang:
Disentangled Differentiable Network Pruning. 328-345 - Sheng Xu, Yanjing Li, Bohan Zeng, Teli Ma, Baochang Zhang, Xianbin Cao, Peng Gao, Jinhu Lü:
IDa-Det: An Information Discrepancy-Aware Distillation for 1-Bit Detectors. 346-361 - Yizeng Han, Yifan Pu, Zihang Lai, Chaofei Wang, Shiji Song, Junfen Cao, Wenhui Huang, Chao Deng, Gao Huang:
Learning to Weight Samples for Dynamic Early-Exiting Networks. 362-378 - Zhijun Tu, Xinghao Chen, Pengju Ren, Yunhe Wang:
AdaBin: Improving Binary Neural Networks with Adaptive Binary Sets. 379-395 - Mohsen Fayyaz, Soroush Abbasi Koohpayegani, Farnoush Rezaei Jafari, Sunando Sengupta, Hamid Reza Vaezi Joze, Eric Sommerlade, Hamed Pirsiavash, Jürgen Gall:
Adaptive Token Sampling for Efficient Vision Transformers. 396-414 - Christopher Subia-Waud, Srinandan Dasmahapatra:
Weight Fixing Networks. 415-431 - Zhuofan Zong, Kunchang Li, Guanglu Song, Yali Wang, Yu Qiao, Biao Leng, Yu Liu:
Self-slimmed Vision Transformer. 432-448 - Biao Qian, Yang Wang, Hongzhi Yin, Richang Hong, Meng Wang:
Switchable Online Knowledge Distillation. 449-466 - Hadi M. Dolatabadi, Sarah M. Erfani, Christopher Leckie:
ℓ ∞-Robustness and Beyond: Unleashing Efficient Adversarial Training. 467-483 - Tianli Zhao, Xi Sheryl Zhang, Wentao Zhu, Jiaxing Wang, Sen Yang, Ji Liu, Jian Cheng:
Multi-granularity Pruning for Model Acceleration on Mobile Devices. 484-501 - Naoki Okamoto, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi:
Deep Ensemble Learning by Diverse Knowledge Distillation for Fine-Grained Object Classification. 502-518 - Hyundong Jin, Eunwoo Kim:
Helpful or Harmful: Inter-task Association in Continual Learning. 519-535 - Xingrun Xing, Yangguang Li, Wei Li, Wenrui Ding, Yalong Jiang, Yufeng Wang, Jing Shao, Chunlei Liu, Xianglong Liu:
Towards Accurate Binary Neural Networks via Modeling Contextual Dependencies. 536-552 - Chien-Yu Lin, Anish Prabhu, Thomas Merth, Sachin Mehta, Anurag Ranjan, Maxwell Horton, Mohammad Rastegari:
SPIN: An Empirical Evaluation on Sharing Parameters of Isotropic Networks. 553-568 - Seunghyun Lee, Byung Cheol Song:
Ensemble Knowledge Guided Sub-network Search and Fine-Tuning for Filter Pruning. 569-585 - Yuzhang Shang, Dan Xu, Ziliang Zong, Liqiang Nie, Yan Yan:
Network Binarization via Contrastive Learning. 586-602 - Yuzhang Shang, Dan Xu, Bin Duan, Ziliang Zong, Liqiang Nie, Yan Yan:
Lipschitz Continuity Retained Binary Neural Network. 603-619 - Zhenglun Kong, Peiyan Dong, Xiaolong Ma, Xin Meng, Wei Niu, Mengshu Sun, Xuan Shen, Geng Yuan, Bin Ren, Hao Tang, Minghai Qin, Yanzhi Wang:
SPViT: Enabling Faster Vision Transformers via Latency-Aware Soft Token Pruning. 620-640 - Ryan Humble, Maying Shen, Jorge Albericio Latorre, Eric Darve, José M. Álvarez:
Soft Masking for Cost-Constrained Channel Pruning. 641-657 - Sangyun Oh, Hyeonuk Sim, Jounghyun Kim, Jongeun Lee:
Non-uniform Step Size Quantization for Accurate Post-training Quantization. 658-673 - Haoran You, Baopu Li, Zhanyi Sun, Xu Ouyang, Yingyan Lin:
SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning. 674-690 - Yi Sun, Jian Li, Xin Xu:
Meta-GF: Training Dynamic-Depth Neural Networks Harmoniously. 691-708 - Sayeed Shafayet Chowdhury, Nitin Rathi, Kaushik Roy:
Towards Ultra Low Latency Spiking Neural Networks for Vision and Sequential Tasks Using Temporal Pruning. 709-726 - Kirill Solodskikh, Vladimir Chikin, Ruslan Aydarkhanov, Dehua Song, Irina Zhelavskaya, Jiansheng Wei:
Towards Accurate Network Quantization with Equivalent Smooth Regularizer. 727-742
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