| 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 | 4142 | 2017 |
| Holistically-Nested Edge Detection S Xie, Z Tu International Conference on Computer Vision (ICCV), 2015, 1395-1403, 2015 | 2066 | 2015 |
| Deeply-Supervised Nets CY Lee*, S Xie*, P Gallagher, Z Zhang, Z Tu Artificial Intelligence and Statistics (AISTATS), 2015, 2014 | 1704 | 2014 |
| 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 | 932 | 2020 |
| 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 | 545* | 2018 |
| 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 | 198 | 2019 |
| 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 | 165 | 2014 |
| Attentional ShapeContextNet for Point Cloud Recognition S Xie, S Liu, Z Chen, Z Tu Computer Vision and Pattern Recognition (CVPR), 2018, 2018 | 130 | 2018 |
| Decoupling representation and classifier for long-tailed recognition B Kang, S Xie, M Rohrbach, Z Yan, A Gordo, J Feng, Y Kalantidis arXiv preprint arXiv:1910.09217, 2019 | 99 | 2019 |
| 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 | 54 | 2012 |
| 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 | 50 | 2020 |
| Top-Down Learning for Structured Labeling with Convolutional Pseudoprior S Xie, X Huang, Z Tu European Conference on Computer Vision (ECCV), 2016, 2016 | 45* | 2016 |
| 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 | 37 | 2019 |
| Multi-Task Co-Clustering via Nonnegative Matrix Factorization S Xie, H Lu, Y He International Conference on Pattern Recognition (ICPR), 2012, 2012 | 30 | 2012 |
| 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 | 22 | 2020 |
| Pairwise Constrained Concept Factorization for Data Representation Y He, H Lu, L Huang, S Xie Neural Networks 52, 1-17, 2013 | 19 | 2013 |
| Sample-Efficient Neural Architecture Search by Learning Actions for Monte Carlo Tree Search L Wang, S Xie, T Li, R Fonseca, Y Tian IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 18* | 2021 |
| Graph structure of neural networks J You, J Leskovec, K He, S Xie International Conference on Machine Learning, 10881-10891, 2020 | 18 | 2020 |
| Semi-Supervised Non-Negative Matrix Factorization for Image Clustering with Graph Laplacian Y He, H Lu, S Xie Multimedia tools and applications 72 (2), 1441-1463, 2013 | 15 | 2013 |
| 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 | 14 | 2020 |
Zhuowen TuProfessor, Cognitive Science, Computer Science&Engineering, UC San DiegoVerified email at ucsd.edu
