Squeeze-and-excitation networks J Hu, L Shen, G Sun IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 7132-7141, 2018 | 26123 | 2018 |
Squeeze-and-excitation networks J Hu, L Shen, G Sun, S Albanie, E Wu IEEE transactions on pattern analysis and machine intelligence 42 (8), 2011-2023, 2019 | 1236* | 2019 |
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 | 575 | 2018 |
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 | 298 | 2016 |
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 | 261 | 2021 |
Squeeze-and-excitation networks (2017) J Hu, L Shen, G Sun arXiv preprint arXiv:1709.01507, 2017 | 66 | 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 | 25 | 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 | 19 | 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 | 6 | 2023 |
Elastic Aggregation for Federated Optimization D Chen*, J Hu*, VJK Tan, E Wu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023 | 4* | 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 | 4 | 2022 |
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), 0 | 1* | |
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 | | 2023 |
Domain-Invariant Representation Learning with Global and Local Consistency W Qiang, J Li, J Hu, B Su, C Zheng, H Xiong | | 2021 |
Supplementary Materials for Elastic Aggregation for Federated Optimization D Chen, J Hu, VJ Tan, X Wei, E Wu | | |