| Squeeze-and-excitation networks J Hu, L Shen, G Sun IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 7132-7141, 2018 | 38564 | 2018 |
| Squeeze-and-excitation networks J Hu, L Shen, G Sun, S Albanie, E Wu IEEE transactions on pattern analysis and machine intelligence (TPAMI) 42 (8 …, 2020 | 1538* | 2020 |
| Gather-excite: Exploiting feature context in convolutional neural networks J Hu, L Shen, S Albanie, G Sun, A Vedaldi Neural Information Processing Systems (NeurIPS), 2018 | 803 | 2018 |
| Involution: Inverting the Inherence of Convolution for Visual Recognition D Li, J Hu, C Wang, X Li, Q She, L Zhu, T Zhang, Q Chen IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 | 436 | 2021 |
| A key volume mining deep framework for action recognition W Zhu, J Hu, G Sun, X Cao, Y Qiao IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 1991-1999, 2016 | 318 | 2016 |
| Squeeze-and-excitation networks. arXiv 2017 J Hu, L Shen, S Albanie, G Sun, E Wu arXiv preprint arXiv:1709.01507 7, 2019 | 151 | 2019 |
| Squeeze-and-excitation networks. arXiv J Hu, L Shen, S Albanie, G Sun, E Wu arXiv preprint arXiv:1709.01507, 2017 | 110 | 2017 |
| ALBANIE S, et al. Squeeze-and-excitation networks J Hu, L SHEN IEEE Transactions on Pattern Analysis and Machine Intelligence 42 (8), 2011-2023, 2020 | 89 | 2020 |
| Squeeze-and-excitation networks (2017) J Hu, L Shen, S Albanie, G Sun, E Wu arXiv preprint arXiv:1709.01507 10, 2017 | 75 | 2017 |
| Learning the Superpixel in a Non-iterative and Lifelong Manner L Zhu, Q She, B Zhang, Y Lu, Z Lu, D Li, J Hu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 | 43 | 2021 |
| Kangaroo: A powerful video-language model supporting long-context video input J Liu, Y Wang, H Ma, X Wu, X Ma, X Wei, J Jiao, E Wu, J Hu* arXiv preprint arXiv:2408.15542, 2024 | 34 | 2024 |
| Elastic Aggregation for Federated Optimization D Chen*, J Hu*, VJK Tan, E Wu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023 | 32 | 2023 |
| Unifying nonlocal blocks for neural networks L Zhu, Q She, D Li, Y Lu, X Kang, J Hu, C Wang International Conference on Computer Vision (ICCV), 12292-12301, 2021 | 29 | 2021 |
| OpenFed: A comprehensive and versatile open-source federated learning framework D Chen, V Tan, Z Lu, E Wu, J Hu* IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2023 | 12 | 2023 |
| Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective Q Ji, J Li, J Hu, R Wang, C Zheng, F Xu AAAI Conference on Artificial Intelligence (AAAI), 2024 | 8 | 2024 |
| Elastic-Link for Binarized Neural Network J Hu, Z Wu, V Tan, Z Lu, M Zeng, E Wu AAAI Conference on Artificial Intelligence (AAAI), 2022 | 6 | 2022 |
| Self-Supervised Representation Learning with Meta Comprehensive Regularization H Guo, Y Ba, J Hu, L Si, W Qiang, L Shi AAAI Conference on Artificial Intelligence (AAAI), 2024 | 5 | 2024 |
| Intriguing property and counterfactual explanation of gan for remote sensing image generation X Su, W Qiang, J Hu, F Wu, C Zheng, F Sun International Journal of Computer Vision (IJCV), 2024 | 4 | 2024 |
| Bag of Tricks with Quantized Convolutional Neural Networks for image classification J Hu, M Zeng, E Wu ICASSP, 2023 | 3 | 2023 |
| RDPM: Solve Diffusion Probabilistic Models via Recurrent Token Prediction X Wu, J Hu*, X Wei arXiv preprint arXiv:2412.18390, 2024 | 1 | 2024 |
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