| Momentum Contrast for Unsupervised Visual Representation Learning K He, H Fan, Y Wu, S Xie, R Girshick Computer Vision and Pattern Recognition (CVPR), 2020, 2020 | 18476 | 2020 |
| 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 | 16096 | 2017 |
| Masked Autoencoders are Scalable Vision Learners K He, X Chen, S Xie, Y Li, P Dollár, R Girshick Computer Vision and Pattern Recognition (CVPR), 2022, 2022 | 13182 | 2022 |
| A ConvNet for the 2020s Z Liu, H Mao, CY Wu, C Feichtenhofer, T Darrell, S Xie Computer Vision and Pattern Recognition (CVPR), 2022, 2022 | 11438 | 2022 |
| Scalable Diffusion Models with Transformers W Peebles, S Xie International Conference on Computer Vision (ICCV), 2023, 2023 | 5099 | 2023 |
| Holistically-Nested Edge Detection S Xie, Z Tu International Conference on Computer Vision (ICCV), 2015, 2015 | 5030 | 2015 |
| Deeply-Supervised Nets CY Lee*, S Xie*, P Gallagher, Z Zhang, Z Tu Artificial Intelligence and Statistics (AISTATS), 2015, 2014 | 3243 | 2014 |
| An Empirical Study of Training Self-supervised Vision Transformers X Chen*, S Xie*, K He International Conference on Computer Vision (ICCV), 2021, 2021 | 2707 | 2021 |
| Rethinking Spatiotemporal Feature Learning: Speed-accuracy Trade-offs in Video Classification S Xie, C Sun, J Huang, Z Tu, K Murphy European Conference on Computer Vision (ECCV), 2018, 2018 | 1916 | 2018 |
| ConvNeXt v2: Co-designing and scaling convnets with masked autoencoders S Woo, S Debnath, R Hu, X Chen, Z Liu, IS Kweon, S Xie Computer Vision and Pattern Recognition (CVPR), 2023, 2023 | 1854 | 2023 |
| Decoupling Representation and Classifier for Long-tailed Recognition B Kang, S Xie, M Rohrbach, Z Yan, A Gordo, J Feng, Y Kalantidis International Conference on Learning Representations (ICLR), 2020, 2019 | 1824 | 2019 |
| Masked Feature Prediction for Self-Supervised Visual Pre-training C Wei, H Fan, S Xie, CY Wu, A Yuille, C Feichtenhofer Computer Vision and Pattern Recognition (CVPR), 2022, 2022 | 938 | 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 (ECCV), 2020, 2020 | 893 | 2020 |
| Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs S Tong, E Brown, P Wu, S Woo, M Middepogu, SC Akula, J Yang, S Yang, ... Neural Information Processing Systems (NeurIPS), 2024, 2024 | 707 | 2024 |
| SLIP: Self-Supervision meets Language-Image Pre-training N Mu, A Kirillov, D Wagner, S Xie European Conference on Computer Vision (ECCV), 2022, 2022 | 657 | 2022 |
| Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs S Tong, Z Liu, Y Zhai, Y Ma, Y LeCun, S Xie Computer Vision and Pattern Recognition (CVPR), 2024, 2024 | 644 | 2024 |
| Exploring Randomly Wired Neural Networks for Image Recognition S Xie, A Kirillov, R Girshick, K He International Conference on Computer Vision (ICCV), 2019, 2019 | 495 | 2019 |
| Attentional ShapeContextNet for Point Cloud Recognition S Xie, S Liu, Z Chen, Z Tu Computer Vision and Pattern Recognition (CVPR), 2018, 2018 | 446 | 2018 |
| SIT: Exploring flow and diffusion-based generative models with scalable interpolant transformers N Ma, M Goldstein, MS Albergo, NM Boffi, E Vanden-Eijnden, S Xie European Conference on Computer Vision (ECCV), 2024, 2024 | 441 | 2024 |
| 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, ... Computer Vision and Pattern Recognition (CVPR), 2020, 2020 | 439 | 2020 |
Zhuowen TuProfessor, Cognitive Science, Computer Science&Engineering, UC San DiegoVerified email at ucsd.edu
