| Tokens-to-token vit: Training vision transformers from scratch on imagenet L Yuan, Y Chen, T Wang, W Yu, Y Shi, Z Jiang, FEH Tay, J Feng, S Yan ICCV 2021, 2021 | 974 | 2021 |
| All tokens matter: Token labeling for training better vision transformers ZH Jiang, Q Hou, L Yuan, D Zhou, Y Shi, X Jin, A Wang, J Feng Advances in Neural Information Processing Systems 34, 18590-18602, 2021 | 124* | 2021 |
| Leveraging instance-, image-and dataset-level information for weakly supervised instance segmentation Y Liu, YH Wu, PS Wen, YJ Shi, Y Qiu, MM Cheng IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020 | 95 | 2020 |
| Rethinking the usage of batch normalization and dropout in the training of deep neural networks G Chen, P Chen, Y Shi, CY Hsieh, B Liao, S Zhang arXiv preprint arXiv:1905.05928, 2019 | 60 | 2019 |
| Refiner: Refining Self-attention for Vision Transformers D Zhou, Y Shi, B Kang, W Yu, Z Jiang, Y Li, X Jin, Q Hou, J Feng arXiv preprint arXiv:2106.03714, 2021 | 35 | 2021 |
| Continual Learning via Bit-Level Information Preserving Y Shi, L Yuan, Y Chen, J Feng CVPR 2021, 2021 | 15 | 2021 |
| Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning Y Shi, K Zhou, J Liang, Z Jiang, J Feng, P Torr, S Bai, VYF Tan CVPR 2022, 2022 | 7 | 2022 |
| Understanding adversarial behavior of dnns by disentangling non-robust and robust components in performance metric Y Shi, B Liao, G Chen, Y Liu, MM Cheng, J Feng arXiv preprint arXiv:1906.02494, 2019 | 2 | 2019 |
| Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning Y Shi, J Liang, W Zhang, VYF Tan, S Bai International Conference on Learning Representations (ICLR), 2023 | | 2023 |
| Learning Pixel-wise Labeling from the Internet without Human Interaction Y Liu, Y Shi, JW Bian, L Zhang, MM Cheng, J Feng arXiv preprint arXiv:1805.07548, 2018 | | 2018 |
Jiashi FengByteDance Inc.在 bytedance.com 的电子邮件经过验证
