| Ghostnet: More features from cheap operations K Han, Y Wang, Q Tian, J Guo, C Xu, C Xu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 3711 | 2020 |
| A survey on vision transformer K Han, Y Wang, H Chen, X Chen, J Guo, Z Liu, Y Tang, A Xiao, C Xu, ... IEEE transactions on pattern analysis and machine intelligence 45 (1), 87-110, 2022 | 2721* | 2022 |
| Pre-trained image processing transformer H Chen, Y Wang, T Guo, C Xu, Y Deng, Z Liu, S Ma, C Xu, C Xu, W Gao CVPR, 12299-12310, 2021 | 2010 | 2021 |
| Transformer in transformer K Han, A Xiao, E Wu, J Guo, C Xu, Y Wang Advances in neural information processing systems 34, 15908-15919, 2021 | 1782 | 2021 |
| Cmt: Convolutional neural networks meet vision transformers J Guo, K Han, H Wu, Y Tang, X Chen, Y Wang, C Xu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 809 | 2022 |
| Data-Free Learning of Student Networks H Chen, Y Wang, C Xu, Z Yang, C Liu, B Shi, C Xu, C Xu, Q Tian ICCV, 3514-3522, 2019 | 423 | 2019 |
| Vision gnn: An image is worth graph of nodes K Han, Y Wang, J Guo, Y Tang, E Wu Advances in neural information processing systems 35, 8291-8303, 2022 | 358 | 2022 |
| Post-training quantization for vision transformer Z Liu, Y Wang, K Han, W Zhang, S Ma, W Gao Advances in Neural Information Processing Systems 34, 28092-28103, 2021 | 338 | 2021 |
| CARS: Continuous Evolution for Efficient Neural Architecture Search Z Yang, Y Wang, X Chen, B Shi, C Xu, C Xu, Q Tian, C Xu CVPR, 1829-1838, 2020 | 291 | 2020 |
| GhostNetv2: Enhance cheap operation with long-range attention Y Tang, K Han, J Guo, C Xu, C Xu, Y Wang Advances in Neural Information Processing Systems 35, 9969-9982, 2022 | 290 | 2022 |
| AdderNet: Do we really need multiplications in deep learning? H Chen, Y Wang, C Xu, B Shi, C Xu, Q Tian, C Xu CVPR, 1468-1477, 2020 | 263 | 2020 |
| Distilling object detectors via decoupled features J Guo, K Han, Y Wang, H Wu, X Chen, C Xu, C Xu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 252 | 2021 |
| Autoencoder Inspired Unsupervised Feature Selection K Han, Y Wang, C Zhang, C Li, C Xu IEEE ICASSP, 2941-2945, 2018 | 215 | 2018 |
| CNNpack: packing convolutional neural networks in the frequency domain Y Wang, C Xu, S You, D Tao, C Xu NeurIPS, 253-261, 2016 | 213 | 2016 |
| Gold-YOLO: Efficient object detector via gather-and-distribute mechanism C Wang, W He, Y Nie, J Guo, C Liu, Y Wang, K Han Advances in Neural Information Processing Systems 36, 2024 | 202 | 2024 |
| Scop: Scientific control for reliable neural network pruning Y Tang, Y Wang, Y Xu, D Tao, C Xu, C Xu, C Xu Advances in Neural Information Processing Systems 33, 10936-10947, 2020 | 194 | 2020 |
| Patch slimming for efficient vision transformers Y Tang, K Han, Y Wang, C Xu, J Guo, C Xu, D Tao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 193 | 2022 |
| Multimodal token fusion for vision transformers Y Wang, X Chen, L Cao, W Huang, F Sun, Y Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 174 | 2022 |
| Efficient residual dense block search for image super-resolution D Song, C Xu, X Jia, Y Chen, C Xu, Y Wang AAAI, 2020, 2020 | 159 | 2020 |
| An image patch is a wave: Phase-aware vision mlp Y Tang, K Han, J Guo, C Xu, Y Li, C Xu, Y Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 140 | 2022 |
Kai Han（韩凯）Noah's Ark Lab, Huawei TechnologiesVerified email at huawei.com
