| Controllable text generation Z Hu, Z Yang, X Liang, R Salakhutdinov, EP Xing arXiv preprint arXiv:1703.00955 4, 2017 | 1307* | 2017 |
| Is faster R-CNN doing well for pedestrian detection? L Zhang, L Lin, X Liang, K He Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 1087 | 2016 |
| Perceptual generative adversarial networks for small object detection J Li, X Liang, Y Wei, T Xu, J Feng, S Yan Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 1001 | 2017 |
| Scale-aware fast R-CNN for pedestrian detection J Li, X Liang, SM Shen, T Xu, J Feng, S Yan IEEE transactions on Multimedia 20 (4), 985-996, 2017 | 988 | 2017 |
| Object region mining with adversarial erasing: A simple classification to semantic segmentation approach Y Wei, J Feng, X Liang, MM Cheng, Y Zhao, S Yan Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 978 | 2017 |
| Look into person: Joint body parsing & pose estimation network and a new benchmark X Liang, K Gong, X Shen, L Lin IEEE transactions on pattern analysis and machine intelligence 41 (4), 871-885, 2018 | 890* | 2018 |
| Stc: A simple to complex framework for weakly-supervised semantic segmentation Y Wei, X Liang, Y Chen, X Shen, MM Cheng, J Feng, Y Zhao, S Yan IEEE transactions on pattern analysis and machine intelligence 39 (11), 2314 …, 2016 | 662 | 2016 |
| FILIP: Fine-grained Interactive Language-Image Pre-Training L Yao, R Huang, L Hou, G Lu, M Niu, H Xu, X Liang, Z Li, X Jiang, C Xu ICLR 2022, 2021 | 597 | 2021 |
| Meta r-cnn: Towards general solver for instance-level low-shot learning X Yan, Z Chen, A Xu, X Wang, X Liang, L Lin Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 580 | 2019 |
| Poseidon: An efficient communication architecture for distributed deep learning on {GPU} clusters H Zhang, Z Zheng, S Xu, W Dai, Q Ho, X Liang, Z Hu, J Wei, P Xie, ... 2017 USENIX Annual Technical Conference (USENIX ATC 17), 181-193, 2017 | 504* | 2017 |
| Voxel Transformer for 3D Object Detection J Mao, Y Xue, M Niu, H Bai, J Feng, X Liang, H Xu, C Xu ICCV 2021, 2021 | 483 | 2021 |
| Toward characteristic-preserving image-based virtual try-on network B Wang, H Zheng, X Liang, Y Chen, L Lin, M Yang Proceedings of the European conference on computer vision (ECCV), 589-604, 2018 | 465 | 2018 |
| Semantic object parsing with graph lstm X Liang, X Shen, J Feng, L Lin, S Yan Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 457 | 2016 |
| Dual motion GAN for future-flow embedded video prediction X Liang, L Lee, W Dai, EP Xing proceedings of the IEEE international conference on computer vision, 1744-1752, 2017 | 454 | 2017 |
| Hybrid retrieval-generation reinforced agent for medical image report generation Y Li, X Liang, Z Hu, EP Xing Advances in neural information processing systems 31, 2018 | 410 | 2018 |
| Instance-level human parsing via part grouping network K Gong, X Liang, Y Li, Y Chen, M Yang, L Lin Proceedings of the European conference on computer vision (ECCV), 770-785, 2018 | 402 | 2018 |
| Rethinking knowledge graph propagation for zero-shot learning M Kampffmeyer, Y Chen, X Liang, H Wang, Y Zhang, EP Xing Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 384 | 2019 |
| Peak-piloted deep network for facial expression recognition X Zhao, X Liang, L Liu, T Li, Y Han, N Vasconcelos, S Yan Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 381 | 2016 |
| Human parsing with contextualized convolutional neural network X Liang, C Xu, X Shen, J Yang, S Liu, J Tang, L Lin, S Yan Proceedings of the IEEE international conference on computer vision, 1386-1394, 2015 | 354 | 2015 |
| Cirl: Controllable imitative reinforcement learning for vision-based self-driving X Liang, T Wang, L Yang, E Xing Proceedings of the European conference on computer vision (ECCV), 584-599, 2018 | 342 | 2018 |
Liang LinFellow of IEEE/IAPR, Research Director of Peng Cheng Laboratory, Professor of Computer Science, SYSUBestätigte E-Mail-Adresse bei ieee.org
