| Smallbignet: Integrating core and contextual views for video classification X Li, Y Wang, Z Zhou, Y Qiao Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 113 | 2020 |
| CT-Net: Channel Tensorization Network for Video Classification K Li, X Li, Y Wang, J Wang, Y Qiao ICLR2021, 2021 | 60 | 2021 |
| An Inverse Scaling Law for CLIP Training X Li, Z Wang, C Xie Advances in Neural Information Processing Systems (NeurIPS), 2023, 2023 | 24 | 2023 |
| Unleashing the power of visual prompting at the pixel level J Wu, X Li, C Wei, H Wang, A Yuille, Y Zhou, C Xie arXiv preprint arXiv:2212.10556, 2022 | 19 | 2022 |
| 3d transunet: Advancing medical image segmentation through vision transformers J Chen, J Mei, X Li, Y Lu, Q Yu, Q Wei, X Luo, Y Xie, E Adeli, Y Wang, ... arXiv preprint arXiv:2310.07781, 2023 | 16 | 2023 |
| Fast advprop J Mei, Y Han, Y Bai, Y Zhang, Y Li, X Li, A Yuille, C Xie International Conference on Learning Representations (ICLR), 2022, 2022 | 10 | 2022 |
| CLIPA-v2: Scaling CLIP Training with 81.1% Zero-shot ImageNet Accuracy within a\$10,000 Budget; An Extra\$4,000 Unlocks 81.8% Accuracy X Li, Z Wang, C Xie NeurIPS R0-FoMo Workshop, 2023, 2023 | 7 | 2023 |
| Learning to bootstrap for combating label noise Y Zhou, X Li, F Liu, X Chen, L Yu, C Xie, MP Lungren, L Xing arXiv preprint arXiv:2202.04291, 2022 | 5 | 2022 |
| Pose-guided Generative Adversarial Net for Novel View Action Synthesis X Li, J Zhang, K Li, S Vyas, YS Rawat WACV2022, 2021 | 4 | 2021 |
| Consistency-guided Meta-Learning for Bootstrapping Semi-Supervised Medical Image Segmentation Q Wei, L Yu, X Li, W Shao, C Xie, L Xing, Y Zhou Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023, 2023 | 2 | 2023 |
| Mitigating lies in vision-language models J Li, X Li, C Xie NeurIPS ML Safety Workshop, 2022 | 2 | 2022 |
| 3D-TransUNet for Brain Metastases Segmentation in the BraTS2023 Challenge S Yang, X Li, J Mei, J Chen, C Xie, Y Zhou arXiv preprint arXiv:2403.15735, 2024 | 1 | 2024 |
| Meta-Learning for Bootstrapping Medical Image Segmentation from Imperfect Supervision Q Wei, L Yu, X Li, W Shao, C Xie, L Xing, Y Zhou | 1 | 2023 |
| In Defense of Image Pre-Training for Spatiotemporal Recognition X Li, H Wang, C Wei, J Mei, A Yuille, Y Zhou, C Xie European Conference on Computer Vision (ECCV), 2022, 2022 | 1 | 2022 |
| What If We Recaption Billions of Web Images with LLaMA-3? X Li, H Tu, M Hui, Z Wang, B Zhao, J Xiao, S Ren, J Mei, Q Liu, H Zheng, ... arXiv preprint arXiv:2406.08478, 2024 | | 2024 |
| Autoregressive Pretraining with Mamba in Vision S Ren, X Li, H Tu, F Wang, F Shu, L Zhang, J Mei, L Yang, P Wang, ... arXiv preprint arXiv:2406.07537, 2024 | | 2024 |
| Scaling White-Box Transformers for Vision J Yang, X Li, D Pai, Y Zhou, Y Ma, Y Yu, C Xie arXiv preprint arXiv:2405.20299, 2024 | | 2024 |
| L2B: Learning to Bootstrap Robust Models for Combating Label Noise Y Zhou, X Li, F Liu, Q Wei, X Chen, L Yu, C Xie, MP Lungren, L Xing Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
| Revisiting Adversarial Training at Scale Z Wang, X Li, H Zhu, C Xie Computer Vision and Pattern Recognition (CVPR), 2024, 2024 | | 2024 |
| MAE are Secretly Efficient Learners Z Wei, C Wei, J Mei, Z Wang, X Li, H Wang, A Yuille, Y Zhou, C Xie | | |
Cihang XieAssistant Professor, University of California, Santa Cruz在 ucsc.edu 的电子邮件经过验证
