| Return of frustratingly easy domain adaptation B Sun, J Feng, K Saenko Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016 | 1497 | 2016 |
| Tokens-to-token vit: Training vision transformers from scratch on imagenet L Yuan, Y Chen, T Wang, W Yu, Y Shi, ZH Jiang, FEH Tay, J Feng, S Yan Proceedings of the IEEE/CVF international conference on computer vision, 558-567, 2021 | 874 | 2021 |
| Coordinate attention for efficient mobile network design Q Hou, D Zhou, J Feng Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 820 | 2021 |
| Dual path networks Y Chen, J Li, H Xiao, X Jin, S Yan, J Feng Advances in neural information processing systems 30, 2017 | 805 | 2017 |
| Scale-aware Fast R-CNN for Pedestrian Detection J Li, X Liang, SM Shen, T Xu, J Feng, S Yan https://arxiv.org/abs/1510.08160, 2016 | 748 | 2016 |
| Deep joint rain detection and removal from a single image W Yang, RT Tan, J Feng, J Liu, Z Guo, S Yan Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 739 | 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 | 704 | 2017 |
| A simple pooling-based design for real-time salient object detection JJ Liu, Q Hou, MM Cheng, J Feng, J Jiang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 683 | 2019 |
| 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 | 642 | 2017 |
| 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 | 625 | 2019 |
| End-to-end comparative attention networks for person re-identification H Liu, J Feng, M Qi, J Jiang, S Yan IEEE Transactions on Image Processing 26 (7), 3492-3506, 2017 | 606 | 2017 |
| Natural language object retrieval R Hu, H Xu, M Rohrbach, J Feng, K Saenko, T Darrell Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 539 | 2016 |
| 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 | 531 | 2016 |
| Panet: Few-shot image semantic segmentation with prototype alignment K Wang, JH Liew, Y Zou, D Zhou, J Feng proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 509 | 2019 |
| Tensor robust principal component analysis with a new tensor nuclear norm C Lu, J Feng, Y Chen, W Liu, Z Lin, S Yan IEEE transactions on pattern analysis and machine intelligence 42 (4), 925-938, 2019 | 495 | 2019 |
| Revisiting dilated convolution: A simple approach for weakly-and semi-supervised semantic segmentation Y Wei, H Xiao, H Shi, Z Jie, J Feng, TS Huang Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 483 | 2018 |
| Few-shot object detection via feature reweighting B Kang, Z Liu, X Wang, F Yu, J Feng, T Darrell Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 479 | 2019 |
| Adversarial complementary learning for weakly supervised object localization X Zhang, Y Wei, J Feng, Y Yang, TS Huang Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 472 | 2018 |
| A^ 2-nets: Double attention networks Y Chen, Y Kalantidis, J Li, S Yan, J Feng Advances in neural information processing systems 31, 2018 | 463 | 2018 |
| Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation J Liang, D Hu, J Feng International Conference on Machine Learning, 6028-6039, 2020 | 457 | 2020 |
Shuicheng Yan, Fellow of AAAI, ACM,...Sea AI Lab; previously NUS, SingaporeVerified email at sea.com
