| Transfer Feature Learning with Joint Distribution Adaptation M Long, J Wang, G Ding, J Sun, PS Yu IEEE ICCV, 2013 | 2192 | 2013 |
| Repvgg: Making vgg-style convnets great again X Ding, X Zhang, N Ma, J Han, G Ding, J Sun Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 2009 | 2021 |
| Scaling up your kernels to 31x31: Revisiting large kernel design in cnns X Ding, X Zhang, J Han, G Ding Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 988 | 2022 |
| Transfer joint matching for unsupervised domain adaptation M Long, J Wang, G Ding, J Sun, PS Yu Proceedings of the IEEE conference on computer vision and pattern …, 2014 | 840 | 2014 |
| Acnet: Strengthening the kernel skeletons for powerful cnn via asymmetric convolution blocks X Ding, Y Guo, G Ding, J Han Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 833 | 2019 |
| Collective Matrix Factorization Hashing for Multimodal Data G Ding, Y Guo, J Zhou Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 708 | 2014 |
| Adaptation Regularization: A General Framework for Transfer Learning M Long, J Wang, G Ding, SJ Pan, P St Yu IEEE Transactions on Knowledge and Data Engineering, 1, 2013 | 688 | 2013 |
| Semantics-preserving hashing for cross-view retrieval Z Lin, G Ding, M Hu, J Wang Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 595 | 2015 |
| Latent semantic sparse hashing for cross-modal similarity search J Zhou, G Ding, Y Guo Proceedings of the 37th international ACM SIGIR conference on Research …, 2014 | 479 | 2014 |
| Imram: Iterative matching with recurrent attention memory for cross-modal image-text retrieval H Chen, G Ding, X Liu, Z Lin, J Liu, J Han Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 407 | 2020 |
| Yolov10: Real-time end-to-end object detection A Wang, H Chen, L Liu, K Chen, Z Lin, J Han, G Ding arXiv preprint arXiv:2405.14458, 2024 | 395 | 2024 |
| Diverse branch block: Building a convolution as an inception-like unit X Ding, X Zhang, J Han, G Ding Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 338 | 2021 |
| Learning from multiple experts: Self-paced knowledge distillation for long-tailed classification L Xiang, G Ding, J Han Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 324 | 2020 |
| Transfer Sparse Coding for Robust Image Representation M Long, G Ding, J Wang, J Sun, Y Guo, PS Yu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013 | 236 | 2013 |
| Transfer Learning with Graph Co-Regularization QY Mingsheng Long, Jianmin Wang, Guiguang Ding, Dou IEEE Transactions on Knowledge and Data Engineering (TKDE), 2013 | 231* | 2013 |
| Centripetal sgd for pruning very deep convolutional networks with complicated structure X Ding, G Ding, Y Guo, J Han Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 229 | 2019 |
| Large-scale cross-modality search via collective matrix factorization hashing G Ding, Y Guo, J Zhou, Y Gao IEEE Transactions on Image Processing 25 (11), 5427-5440, 2016 | 216 | 2016 |
| Resrep: Lossless cnn pruning via decoupling remembering and forgetting X Ding, T Hao, J Tan, J Liu, J Han, Y Guo, G Ding Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 212 | 2021 |
| Continuous probability distribution prediction of image emotions via multitask shared sparse regression S Zhao, H Yao, Y Gao, R Ji, G Ding IEEE transactions on multimedia 19 (3), 632-645, 2016 | 203 | 2016 |
| Global sparse momentum sgd for pruning very deep neural networks X Ding, X Zhou, Y Guo, J Han, J Liu Advances in Neural Information Processing Systems 32, 2019 | 193 | 2019 |
