| 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 | 7152 | 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 | 3673 | 2020 |
| Holistically-Nested Edge Detection S Xie, Z Tu International Conference on Computer Vision (ICCV), 2015, 1395-1403, 2015 | 2818 | 2015 |
| Deeply-Supervised Nets CY Lee*, S Xie*, P Gallagher, Z Zhang, Z Tu Artificial Intelligence and Statistics (AISTATS), 2015, 2014 | 2111 | 2014 |
| 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 | 973* | 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 | 384 | 2019 |
| 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 | 292 | 2019 |
| 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 | 276 | 2022 |
| An Empirical Study of Training Self-supervised Vision Transformers X Chen*, S Xie*, K He ICCV 2021, 2021 | 243 | 2021 |
| Attentional ShapeContextNet for Point Cloud Recognition S Xie, S Liu, Z Chen, Z Tu Computer Vision and Pattern Recognition (CVPR), 2018, 2018 | 209 | 2018 |
| Hyper-class Augmented and Regularized Deep Learning for Fine-grained Image Classification S Xie, T Yang, X Wang, Y Lin Computer Vision and Pattern Recognition (CVPR), 2015, 2014 | 195 | 2014 |
| 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 | 163 | 2020 |
| 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 | 137 | 2020 |
| A convnet for the 2020s Z Liu, H Mao, CY Wu, C Feichtenhofer, T Darrell, S Xie Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 119 | 2022 |
| On network design spaces for visual recognition I Radosavovic, J Johnson, S Xie, WY Lo, P Dollár Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 73 | 2019 |
| Graph Structure of Neural Networks J You, J Leskovec, K He, S Xie International Conference on Machine Learning, 10881-10891, 2020 | 65 | 2020 |
| Combining Factorization Model and Additive Forest for Collaborative Followee Recommendation T Chen, L Tang, Q Liu, D Yang, S Xie, X Cao, C Wu, E Yao, Z Liu, Z Jiang, ... KDD CUP, 2012, 2012 | 58 | 2012 |
| 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 | 53 | 2022 |
| Top-Down Learning for Structured Labeling with Convolutional Pseudoprior S Xie, X Huang, Z Tu European Conference on Computer Vision (ECCV), 2016, 2016 | 47* | 2016 |
| Are labels necessary for neural architecture search? C Liu, P Dollár, K He, R Girshick, A Yuille, S Xie European Conference on Computer Vision, 798-813, 2020 | 45 | 2020 |
Zhuowen TuProfessor, Cognitive Science, Computer Science&Engineering, UC San DiegoVerified email at ucsd.edu
