| Spindle net: Person re-identification with human body region guided feature decomposition and fusion H Zhao, M Tian, S Sun, J Shao, J Yan, S Yi, X Wang, X Tang Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 447 | 2017 |
| Hydraplus-net: Attentive deep features for pedestrian analysis X Liu, H Zhao, M Tian, L Sheng, J Shao, S Yi, J Yan, X Wang Proceedings of the IEEE international conference on computer vision, 350-359, 2017 | 226 | 2017 |
| Understanding Pedestrian Behaviors from Stationary Crowd Groups S Yi, H Li, X Wang Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on …, 2015 | 159 | 2015 |
| Orientation invariant feature embedding and spatial temporal regularization for vehicle re-identification Z Wang, L Tang, X Liu, Z Yao, S Yi, J Shao, J Yan, S Wang, H Li, X Wang Proceedings of the IEEE International Conference on Computer Vision, 379-387, 2017 | 135 | 2017 |
| Learning deep neural networks for vehicle re-id with visual-spatio-temporal path proposals Y Shen, T Xiao, H Li, S Yi, X Wang Proceedings of the IEEE International Conference on Computer Vision, 1900-1909, 2017 | 135 | 2017 |
| Person re-identification with deep similarity-guided graph neural network Y Shen, H Li, S Yi, D Chen, X Wang Proceedings of the European conference on computer vision (ECCV), 486-504, 2018 | 109 | 2018 |
| Deep group-shuffling random walk for person re-identification Y Shen, H Li, T Xiao, S Yi, D Chen, X Wang Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 89 | 2018 |
| Pedestrian behavior understanding and prediction with deep neural networks S Yi, H Li, X Wang European Conference on Computer Vision, 263-279, 2016 | 79 | 2016 |
| Fd-gan: Pose-guided feature distilling gan for robust person re-identification Y Ge, Z Li, H Zhao, G Yin, S Yi, X Wang Advances in neural information processing systems, 1222-1233, 2018 | 75 | 2018 |
| Video person re-identification with competitive snippet-similarity aggregation and co-attentive snippet embedding D Chen, H Li, T Xiao, S Yi, X Wang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 75 | 2018 |
| End-to-end deep kronecker-product matching for person re-identification Y Shen, T Xiao, H Li, S Yi, X Wang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 62 | 2018 |
| Learning monocular depth by distilling cross-domain stereo networks X Guo, H Li, S Yi, J Ren, X Wang Proceedings of the European Conference on Computer Vision (ECCV), 484-500, 2018 | 61 | 2018 |
| Eliminating background-bias for robust person re-identification M Tian, S Yi, H Li, S Li, X Zhang, J Shi, J Yan, X Wang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 53 | 2018 |
| L0 regularized stationary time estimation for crowd group analysis S Yi, X Wang, C Lu, J Jia Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 41 | 2014 |
| Fishnet: A versatile backbone for image, region, and pixel level prediction S Sun, J Pang, J Shi, S Yi, W Ouyang Advances in neural information processing systems, 754-764, 2018 | 39 | 2018 |
| Pedestrian behavior modeling from stationary crowds with applications to intelligent surveillance S Yi, H Li, X Wang IEEE, 2016 | 33 | 2016 |
| Hms-net: Hierarchical multi-scale sparsity-invariant network for sparse depth completion Z Huang, J Fan, S Cheng, S Yi, X Wang, H Li IEEE Transactions on Image Processing 29, 3429-3441, 2019 | 31 | 2019 |
| Visual importance and distortion guided deep image quality assessment framework J Guan, S Yi, X Zeng, WK Cham, X Wang IEEE Transactions on Multimedia 19 (11), 2505-2520, 2017 | 28 | 2017 |
| Pedestrian travel time estimation in crowded scenes S Yi, H Li, X Wang Proceedings of the IEEE International Conference on Computer Vision, 3137-3145, 2015 | 20 | 2015 |
| Regularized Stationary-Time Estimation for Crowd Analysis S Yi, X Wang, C Lu, J Jia, H Li IEEE transactions on pattern analysis and machine intelligence 39 (5), 981-994, 2016 | 17 | 2016 |
Xiaogang WangAssociate Professor of Electronic Engineering, the Chinese University of Hong KongVerified email at ee.cuhk.edu.hk
