| Aggregated Residual Transformations for Deep Neural Networks S Xie, R Girshick, P Dollár, Z Tu, K He Computer Vision and Pattern Recognition (CVPR), 2017, 2017 | 13324 | 2017 |
| Momentum Contrast for Unsupervised Visual Representation Learning K He, H Fan, Y Wu, S Xie, R Girshick Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 13127 | 2020 |
| Masked Autoencoders are Scalable Vision Learners K He, X Chen, S Xie, Y Li, P Dollár, R Girshick Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 7052 | 2022 |
| A ConvNet for the 2020s Z Liu, H Mao, CY Wu, C Feichtenhofer, T Darrell, S Xie CVPR 2022, 11976-11986, 2022 | 5633 | 2022 |
| Holistically-Nested Edge Detection S Xie, Z Tu International Conference on Computer Vision (ICCV), 2015, 1395-1403, 2015 | 4294 | 2015 |
| Deeply-Supervised Nets CY Lee*, S Xie*, P Gallagher, Z Zhang, Z Tu Artificial Intelligence and Statistics (AISTATS), 2015, 2014 | 2868 | 2014 |
| An Empirical Study of Training Self-supervised Vision Transformers X Chen*, S Xie*, K He ICCV 2021, 2021 | 1749 | 2021 |
| Rethinking Spatiotemporal Feature Learning: Speed-accuracy Trade-offs in Video Classification S Xie, C Sun, J Huang, Z Tu, K Murphy Proceedings of the European conference on computer vision (ECCV), 305-321, 2018 | 1611 | 2018 |
| Decoupling Representation and Classifier for Long-tailed Recognition B Kang, S Xie, M Rohrbach, Z Yan, A Gordo, J Feng, Y Kalantidis ICLR 2020, 2019 | 1348 | 2019 |
| Scalable Diffusion Models with Transformers W Peebles, S Xie ICCV 2023, 2023 | 863 | 2023 |
| Masked feature prediction for self-supervised visual pre-training C Wei, H Fan, S Xie, CY Wu, A Yuille, C Feichtenhofer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 657 | 2022 |
| PointContrast: Unsupervised pre-training for 3d point cloud understanding S Xie, J Gu, D Guo, CR Qi, L Guibas, O Litany European Conference on Computer Vision, 574-591, 2020 | 626 | 2020 |
| ConvNeXt v2: Co-designing and scaling convnets with masked autoencoders S Woo, S Debnath, R Hu, X Chen, Z Liu, IS Kweon, S Xie CVPR 2023, 2023 | 625* | 2023 |
| Exploring Randomly Wired Neural Networks for Image Recognition S Xie, A Kirillov, R Girshick, K He Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 449 | 2019 |
| SLIP: Self-supervision meets language-image pre-training N Mu, A Kirillov, D Wagner, S Xie ECCV 2022, 2022 | 421 | 2022 |
| Attentional ShapeContextNet for Point Cloud Recognition S Xie, S Liu, Z Chen, Z Tu Computer Vision and Pattern Recognition (CVPR), 2018, 2018 | 394 | 2018 |
| Fbnetv2: Differentiable neural architecture search for spatial and channel dimensions A Wan, X Dai, P Zhang, Z He, Y Tian, S Xie, B Wu, M Yu, T Xu, K Chen, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 347 | 2020 |
| Rethinking spatiotemporal feature learning for video understanding S Xie, C Sun, J Huang, Z Tu, K Murphy arXiv preprint arXiv:1712.04851 1 (2), 5, 2017 | 292 | 2017 |
| Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts J Hou, B Graham, M Nießner, S Xie CVPR 2021, 2021 | 279 | 2021 |
| Exploring balanced feature spaces for representation learning B Kang, Y Li, S Xie, Z Yuan, J Feng International Conference on Learning Representations, 2020 | 266 | 2020 |
Zhuowen TuProfessor, Cognitive Science, Computer Science&Engineering, UC San DiegoVerified email at ucsd.edu
