| Transfer learning for visual categorization: A survey L Shao, F Zhu, X Li IEEE transactions on neural networks and learning systems 26 (5), 1019-1034, 2014 | 913 | 2014 |
| isaid: A large-scale dataset for instance segmentation in aerial images S Waqas Zamir, A Arora, A Gupta, S Khan, G Sun, F Shahbaz Khan, F Zhu, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 287 | 2019 |
| Attentive region embedding network for zero-shot learning GS Xie, L Liu, X Jin, F Zhu, Z Zhang, J Qin, Y Yao, L Shao Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 284 | 2019 |
| Collaborative learning of semi-supervised segmentation and classification for medical images Y Zhou, X He, L Huang, L Liu, F Zhu, S Cui, L Shao Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 250 | 2019 |
| 3d deep shape descriptor Y Fang, J Xie, G Dai, M Wang, F Zhu, T Xu, E Wong Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 250 | 2015 |
| Weakly-supervised cross-domain dictionary learning for visual recognition F Zhu, L Shao International Journal of Computer Vision 109 (1), 42-59, 2014 | 236 | 2014 |
| Ranet: Ranking attention network for fast video object segmentation Z Wang, J Xu, L Liu, F Zhu, L Shao Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 232 | 2019 |
| Star: A structure and texture aware retinex model J Xu, Y Hou, D Ren, L Liu, F Zhu, M Yu, H Wang, L Shao IEEE Transactions on Image Processing 29, 5022-5037, 2020 | 218 | 2020 |
| Normalization techniques in training dnns: Methodology, analysis and application L Huang, J Qin, Y Zhou, F Zhu, L Liu, L Shao IEEE transactions on pattern analysis and machine intelligence 45 (8), 10173 …, 2023 | 195 | 2023 |
| Relational attention network for crowd counting A Zhang, J Shen, Z Xiao, F Zhu, X Zhen, X Cao, L Shao Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 192 | 2019 |
| Pyramidal convolution: Rethinking convolutional neural networks for visual recognition IC Duta, L Liu, F Zhu, L Shao arXiv preprint arXiv:2006.11538, 2020 | 187 | 2020 |
| One shot learning gesture recognition from rgbd images D Wu, F Zhu, L Shao 2012 IEEE Computer Society Conference on Computer Vision and Pattern …, 2012 | 184 | 2012 |
| Deepshape: Deep learned shape descriptor for 3d shape matching and retrieval J Xie, Y Fang, F Zhu, E Wong Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 178 | 2015 |
| Noisy-as-clean: Learning self-supervised denoising from corrupted image J Xu, Y Huang, MM Cheng, L Liu, F Zhu, Z Xu, L Shao IEEE Transactions on Image Processing 29, 9316-9329, 2020 | 164 | 2020 |
| From handcrafted to learned representations for human action recognition: A survey F Zhu, L Shao, J Xie, Y Fang Image and Vision Computing 55, 42-52, 2016 | 151 | 2016 |
| Improved residual networks for image and video recognition IC Duta, L Liu, F Zhu, L Shao 2020 25th International Conference on Pattern Recognition (ICPR), 9415-9422, 2021 | 150 | 2021 |
| Region graph embedding network for zero-shot learning GS Xie, L Liu, F Zhu, F Zhao, Z Zhang, Y Yao, J Qin, L Shao Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 149 | 2020 |
| Zero-VAE-GAN: Generating unseen features for generalized and transductive zero-shot learning R Gao, X Hou, J Qin, J Chen, L Liu, F Zhu, Z Zhang, L Shao IEEE Transactions on Image Processing 29, 3665-3680, 2020 | 147 | 2020 |
| Deepshape: Deep-learned shape descriptor for 3d shape retrieval J Xie, G Dai, F Zhu, EK Wong, Y Fang IEEE transactions on pattern analysis and machine intelligence 39 (7), 1335-1345, 2016 | 147 | 2016 |
| Learning multi-granular hypergraphs for video-based person re-identification Y Yan, J Qin, J Chen, L Liu, F Zhu, Y Tai, L Shao Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 140 | 2020 |
Ling Shao, Fellow of IEEE/IAPRGeneral Terminus Technologies; Former CEO of IIAI, Initiator/Provost & EVP of MBZUAIVerified email at inceptioniai.org
