| Squeeze-and-excitation networks J Hu, L Shen, G Sun IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 7132-7141, 2018 | 29893 | 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 | 1397* | 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 | 655 | 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 | 324 | 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 | 305 | 2016 |
| Squeeze-and-excitation networks. In 2018 IEEE J Hu, L Shen, G Sun CVF conference on computer vision and pattern recognition, 7132-7141, 2021 | 37 | 2021 |
| 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 | 32 | 2021 |
| 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 | 25 | 2021 |
| Elastic Aggregation for Federated Optimization D Chen*, J Hu*, VJK Tan, E Wu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023 | 8 | 2023 |
| 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 | 7 | 2023 |
| 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 | 5 | 2022 |
| Bag of Tricks with Quantized Convolutional Neural Networks for image classification J Hu, M Zeng, E Wu IEEE International Conference on Acoustics, Speech and Signal Processing …, 2023 | 1 | 2023 |
| Rethinking skip connection model as a learnable Markov chain D Chen*, J Hu*, W Qiang, X Wei, E Wu International Conference on Learning Representations (ICLR), 2022 | 1 | 2022 |
| Real3D: The Curious Case of Neural Scene Degeneration D Chen, J Hu, X Wei, E Wu AAAI Conference on Artificial Intelligence (AAAI), 2024 | | 2024 |
| 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 | | 2024 |
| 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 | | 2024 |
| Domain-Invariant Representation Learning with Global and Local Consistency W Qiang, J Li, J Hu, B Su, C Zheng, H Xiong | | 2021 |
| When Self-Supervised Learning Meets Unbounded Pseudo-Label Generation W Qiang, L Si, J Hu, J Li, C Zheng, F Sun, H Xiong | | |
| Zero-Shot Video Sampling from Image C Dengsheng, J Hu, X Wei | | |
| Supplementary Materials for Elastic Aggregation for Federated Optimization D Chen, J Hu, VJ Tan, X Wei, E Wu | | |
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