| Enhanced computer vision with microsoft kinect sensor: A review J Han, L Shao, D Xu, J Shotton IEEE transactions on cybernetics 43 (5), 1318-1334, 2013 | 2004 | 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 | 1475 | 2021 |
| 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 | 682 | 2019 |
| 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 | 651 | 2022 |
| Sparse representation based multi-sensor image fusion for multi-focus and multi-modality images: A review Q Zhang, Y Liu, RS Blum, J Han, D Tao Information Fusion 40, 57-75, 2018 | 437 | 2018 |
| Gabor convolutional networks S Luan, C Chen, B Zhang, J Han, J Liu IEEE Transactions on Image Processing 27 (9), 4357-4366, 2018 | 382 | 2018 |
| 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 | 334 | 2020 |
| 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 | 265 | 2020 |
| 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 | 238 | 2021 |
| Cross-modality deep feature learning for brain tumor segmentation D Zhang, G Huang, Q Zhang, J Han, J Han, Y Yu Pattern Recognition 110, 107562, 2021 | 209 | 2021 |
| 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 | 204 | 2019 |
| Memory attention networks for skeleton-based action recognition C Li, C Xie, B Zhang, J Han, X Zhen, J Chen IEEE Transactions on Neural Networks and Learning Systems 33 (9), 4800-4814, 2021 | 197 | 2021 |
| RGB-D datasets using microsoft kinect or similar sensors: a survey Z Cai, J Han, L Liu, L Shao Multimedia Tools and Applications 76, 4313-4355, 2017 | 185 | 2017 |
| Automatic video-based human motion analyzer for consumer surveillance system W Lao, J Han IEEE Transactions on Consumer Electronics 55 (2), 591-598, 2009 | 182 | 2009 |
| 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 | 181 | 2019 |
| Cross-view retrieval via probability-based semantics-preserving hashing Z Lin, G Ding, J Han, J Wang IEEE transactions on cybernetics 47 (12), 4342-4355, 2016 | 179 | 2016 |
| RGB-T salient object detection via fusing multi-level CNN features Q Zhang, N Huang, L Yao, D Zhang, C Shan, J Han IEEE Transactions on Image Processing 29, 3321-3335, 2019 | 177 | 2019 |
| Cosaliency detection based on intrasaliency prior transfer and deep intersaliency mining D Zhang, J Han, J Han, L Shao IEEE transactions on neural networks and learning systems 27 (6), 1163-1176, 2015 | 177 | 2015 |
| 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 | 173 | 2021 |
| From zero-shot learning to conventional supervised classification: Unseen visual data synthesis Y Long, L Liu, L Shao, F Shen, G Ding, J Han Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 173 | 2017 |
