| RepVGG: Making VGG-style ConvNets Great Again X Ding, X Zhang, N Ma, J Han, G Ding, J Sun CVPR 2021, 2021 | 1886 | 2021 |
| Scaling up your kernels to 31x31: Revisiting large kernel design in cnns X Ding, X Zhang, J Han, G Ding Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 897 | 2022 |
| ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blocks X Ding, Y Guo, G Ding, J Han International Conference on Computer Vision (ICCV) 2019, 2019 | 797 | 2019 |
| Diverse branch block: Building a convolution as an inception-like unit X Ding, X Zhang, J Han, G Ding Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 320 | 2021 |
| Centripetal sgd for pruning very deep convolutional networks with complicated structure X Ding, G Ding, Y Guo, J Han Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 221 | 2019 |
| Resrep: Lossless cnn pruning via decoupling remembering and forgetting X Ding, T Hao, J Tan, J Liu, J Han, Y Guo, G Ding Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 215 | 2021 |
| Repmlpnet: Hierarchical vision mlp with re-parameterized locality X Ding, H Chen, X Zhang, J Han, G Ding Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 200* | 2022 |
| Global Sparse Momentum SGD for Pruning Very Deep Neural Networks X Ding, G Ding, X Zhou, Y Guo, J Liu, J Han NeurIPS 2019, 2019 | 193 | 2019 |
| Approximated Oracle Filter Pruning for Destructive CNN Width Optimization X Ding, G Ding, Y Guo, J Han, C Yan International Conference on Machine Learning, 1607-1616, 2019 | 137 | 2019 |
| Auto-balanced filter pruning for efficient convolutional neural networks X Ding, G Ding, J Han, S Tang Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 137 | 2018 |
| UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio Video Point Cloud Time-Series and Image Recognition X Ding, Y Zhang, Y Ge, S Zhao, L Song, X Yue, Y Shan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 71* | 2024 |
| Re-parameterizing Your Optimizers rather than Architectures X Ding, H Chen, X Zhang, K Huang, J Han, G Ding ICLR 2023, 2023 | 51 | 2023 |
| What Makes for Good Visual Tokenizers for Large Language Models? G Wang, Y Ge, X Ding, M Kankanhalli, Y Shan arXiv preprint arXiv:2305.12223, 2023 | 24 | 2023 |
| Vl-gpt: A generative pre-trained transformer for vision and language understanding and generation J Zhu, X Ding, Y Ge, Y Ge, S Zhao, H Zhao, X Wang, Y Shan arXiv preprint arXiv:2312.09251, 2023 | 18 | 2023 |
| Seed-x: Multimodal models with unified multi-granularity comprehension and generation Y Ge, S Zhao, J Zhu, Y Ge, K Yi, L Song, C Li, X Ding, Y Shan arXiv preprint arXiv:2404.14396, 2024 | 17 | 2024 |
| Manipulating identical filter redundancy for efficient pruning on deep and complicated cnn T Hao, X Ding, J Han, Y Guo, G Ding IEEE Transactions on Neural Networks and Learning Systems, 2023 | 15* | 2023 |
| Dual-View Ranking with Hardness Assessment for Zero-Shot Learning Y Guo, G Ding, J Han, X Ding, S Zhao, Z Wang, C Yan, Q Dai Proceedings of the AAAI Conference on Artificial Intelligence 33, 8360-8367, 2019 | 14 | 2019 |
| Online vectorized hd map construction using geometry Z Zhang, Y Zhang, X Ding, F Jin, X Yue arXiv preprint arXiv:2312.03341, 2023 | 11 | 2023 |
| Advancing vision transformers with group-mix attention C Ge, X Ding, Z Tong, L Yuan, J Wang, Y Song, P Luo arXiv preprint arXiv:2311.15157, 2023 | 11 | 2023 |
| Evolving Semantic Prototype Improves Generative Zero-Shot Learning S Chen, W Hou, Z Hong, X Ding, Y Song, X You, T Liu, K Zhang ICML 2023, 2023 | 10 | 2023 |
Jungong HanChair Professor in Computer Vision, University of Sheffield, UK, FIAPR, FAAIAПотвърден имейл адрес: sheffield.ac.uk
