| Couplenet: Coupling global structure with local parts for object detection Y Zhu, C Zhao, J Wang, X Zhao, Y Wu, H Lu Proceedings of the IEEE international conference on computer vision, 4126-4134, 2017 | 327 | 2017 |
| Dual super-resolution learning for semantic segmentation L Wang, D Li, Y Zhu, L Tian, Y Shan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 193 | 2020 |
| Attention CoupleNet: Fully convolutional attention coupling network for object detection Y Zhu, C Zhao, H Guo, J Wang, X Zhao, H Lu IEEE Transactions on Image Processing 28 (1), 113-126, 2018 | 159 | 2018 |
| Mst: Masked self-supervised transformer for visual representation Z Li, Z Chen, F Yang, W Li, Y Zhu, C Zhao, R Deng, L Wu, R Zhao, M Tang, ... Advances in Neural Information Processing Systems 34, 13165-13176, 2021 | 127 | 2021 |
| Adaptive class suppression loss for long-tail object detection T Wang, Y Zhu, C Zhao, W Zeng, J Wang, M Tang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 96 | 2021 |
| Dpt: Deformable patch-based transformer for visual recognition Z Chen, Y Zhu, C Zhao, G Hu, W Zeng, J Wang, M Tang Proceedings of the 29th ACM International Conference on Multimedia, 2899-2907, 2021 | 80 | 2021 |
| A novel data augmentation scheme for pedestrian detection with attribute preserving GAN S Liu, H Guo, JG Hu, X Zhao, C Zhao, T Wang, Y Zhu, J Wang, M Tang Neurocomputing 401, 123-132, 2020 | 40 | 2020 |
| Pass: Part-aware self-supervised pre-training for person re-identification K Zhu, H Guo, T Yan, Y Zhu, J Wang, M Tang European conference on computer vision, 198-214, 2022 | 39 | 2022 |
| Univip: A unified framework for self-supervised visual pre-training Z Li, Y Zhu, F Yang, W Li, C Zhao, Y Chen, Z Chen, J Xie, L Wu, R Zhao, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 31 | 2022 |
| Scale-adaptive deconvolutional regression network for pedestrian detection Y Zhu, J Wang, C Zhao, H Guo, H Lu Computer Vision–ACCV 2016: 13th Asian Conference on Computer Vision, Taipei …, 2017 | 25 | 2017 |
| Large batch optimization for object detection: Training coco in 12 minutes T Wang, Y Zhu, C Zhao, W Zeng, Y Wang, J Wang, M Tang Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 16 | 2020 |
| Obj2seq: Formatting objects as sequences with class prompt for visual tasks Z Chen, Y Zhu, Z Li, F Yang, W Li, H Wang, C Zhao, L Wu, R Zhao, ... Advances in Neural Information Processing Systems 35, 2494-2506, 2022 | 15 | 2022 |
| Food det: Detecting foods in refrigerator with supervised transformer network Y Zhu, X Zhao, C Zhao, J Wang, H Lu Neurocomputing 379, 162-171, 2020 | 15 | 2020 |
| C2am loss: Chasing a better decision boundary for long-tail object detection T Wang, Y Zhu, Y Chen, C Zhao, B Yu, J Wang, M Tang Proceedings of the IEEE/CVF Conference on computer vision and pattern …, 2022 | 13 | 2022 |
| Mask guided knowledge distillation for single shot detector Y Zhu, C Zhao, C Han, J Wang, H Lu 2019 IEEE International Conference on Multimedia and Expo (ICME), 1732-1737, 2019 | 10 | 2019 |
| Restoring execution environments of jupyter notebooks. In 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) J Wang, L Li, A Zeller IEEE, 2021 | 8 | 2021 |
| Exploring stochastic autoregressive image modeling for visual representation Y Qi, F Yang, Y Zhu, Y Liu, L Wu, R Zhao, W Li Proceedings of the AAAI Conference on Artificial Intelligence 37 (2), 2074-2081, 2023 | 6 | 2023 |
| Mitigating hallucination in visual language models with visual supervision Z Chen, Y Zhu, Y Zhan, Z Li, C Zhao, J Wang, M Tang arXiv preprint arXiv:2311.16479, 2023 | 5 | 2023 |
| Griffon: Spelling out All Object Locations at Any Granularity with Large Language Models Y Zhan, Y Zhu, Z Chen, F Yang, M Tang, J Wang arXiv preprint arXiv:2311.14552, 2023 | 5 | 2023 |
| Elite Loss for scene text detection X Zhao, C Zhao, H Guo, Y Zhu, M Tang, J Wang Neurocomputing 333, 284-291, 2019 | 5 | 2019 |
