| Ntire 2017 challenge on single image super-resolution: Methods and results R Timofte, E Agustsson, L Van Gool, MH Yang, L Zhang, et al. Computer Vision and Pattern Recognition (CVPR), NTIRE Workshop, 2017 | 2050 | 2017 |
| Metaformer is actually what you need for vision W Yu, M Luo, P Zhou, C Si, Y Zhou, X Wang, J Feng, S Yan Computer Vision and Pattern Recognition (CVPR), 2022 | 1232 | 2022 |
| Mm-vet: Evaluating large multimodal models for integrated capabilities W Yu, Z Yang, L Li, J Wang, K Lin, Z Liu, X Wang, L Wang International Conference on Machine Learning (ICML), 2024 | 617 | 2024 |
| LLM-Pruner: On the Structural Pruning of Large Language Models X Ma, G Fang, X Wang Neural Information Processing Systems (NeurIPS), 2023 | 589 | 2023 |
| On Compressing Deep Models by Low Rank and Sparse Decomposition X Yu, T Liu, X Wang, D Tao Computer Vision and Pattern Recognition (CVPR), 2017 | 550 | 2017 |
| Horizontal pyramid matching for person re-identification Y Fu, Y Wei, Y Zhou, H Shi, H Gao, X Wang, Z Yao, T Huang AAAI Conference on Artificial Intelligence (AAAI), 2019 | 545 | 2019 |
| Wide activation for efficient and accurate image super-resolution J Yu, Y Fan, J Yang, N Xu, Z Wang, X Wang, T Huang arXiv preprint arXiv:1808.08718, 2018 | 516 | 2018 |
| DepGraph: Towards Any Structural Pruning G Fang, X Ma, M Song, MB Mi, X Wang Computer Vision and Pattern Recognition (CVPR), 2023 | 421 | 2023 |
| Ntire 2018 challenge on single image super-resolution: Methods and results R Timofte, S Gu, J Wu, L Van Gool, et al. Computer Vision and Pattern Recognition (CVPR), NTIRE Workshop, 2018 | 402 | 2018 |
| Learning Temporal Dynamics for Video Super-Resolution: A Deep Learning Approach D Liu, Z Wang, Y Fan, X Liu, Z Wang, S Chang, X Wang, TS Huang IEEE Transactions on Image Processing (TIP), 2018 | 352* | 2018 |
| Shunted Self-Attention via Multi-Scale Token Aggregation S Ren, D Zhou, S He, J Feng, X Wang Computer Vision and Pattern Recognition (CVPR), 2022 | 319 | 2022 |
| Distilling Knowledge From Graph Convolutional Networks Y Yang, J Qiu, M Song, D Tao, X Wang Computer Vision and Pattern Recognition (CVPR), 2020 | 309 | 2020 |
| Predicting people’s 3d poses from short sequences B Tekin, X Sun, X Wang, V Lepetit, P Fua arXiv preprint arXiv: 1504.08200, 2015 | 309* | 2015 |
| Inception Transformer C Si, W Yu, P Zhou, Y Zhou, X Wang, S Yan Neural Information Processing Systems (NeurIPS), 2022 | 274 | 2022 |
| CAFE: Learning to Condense Dataset by Aligning Features K Wang, B Zhao, X Peng, Z Zhu, S Yang, S Wang, G Huang, H Bilen, ... Computer Vision and Pattern Recognition (CVPR), 2022 | 272 | 2022 |
| Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning D Lian, D Zhou, J Feng, X Wang Neural Information Processing Systems (NeurIPS), 2022 | 260 | 2022 |
| One-pass multi-task networks with cross-task guided attention for brain tumor segmentation C Zhou, C Ding, X Wang, Z Lu, D Tao IEEE Transactions on Image Processing (TIP), 2020 | 242 | 2020 |
| Structural Pruning for Diffusion Models G Fang, X Ma, X Wang Neural information processing systems (NeurIPS), 2023 | 226* | 2023 |
| Dynamic Instance Normalization for Arbitrary Style Transfer Y Jing, X Liu, Y Ding, X Wang, E Ding, M Song, S Wen AAAI Conference on Artificial Intelligence (AAAI), 2020 | 209 | 2020 |
| Metaformer baselines for vision W Yu, C Si, P Zhou, M Luo, Y Zhou, J Feng, S Yan, X Wang IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024 | 200 | 2024 |
Xingyi YangNational University of SingaporeVerified email at u.nus.edu
