叶茂

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Professor   Supervisor of Doctorate Candidates  

Personal Profile

Mao Ye DPhil (HONG KONG)

Professor

School of Computer Science and Engineering

University of Electronic Science and Technology of China, Chengdu, China

Email: maoye@uestc.edu.cn

 

University education

1999 - 2002 Ph.D., The Chinese University of Hong Kong, Hong Kong, China

1995 - 1998 M.E., University of Electronic Science and Technology of China, Chengdu, China

1991 - 1995 B.E., Sichuan Normal University, Chengdu, China

 

Employment

2002 – Present   Professor in AI, University of Electronic Science and Technology of China

1998 1999        Assistant Engineer, The 29th Research Institute, CETC

 

Selected community services

2015~

Associate Editor, Engineering Applications of Artificial Intelligence,

2024

Senior Program Committee Member, International Joint Conference on Artificial Intelligence

2013 ~

Reviewer, IEEE TMM, TPAMI, TIP, TCybertics, TCSVT, TNNLS, CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, AAAI, IJCAI, PR

 

Selected awards

2023~

Elsevier Highly Cited Chinese Researchers

2017

ICME Best student paper award

 

Selected articles (2019~)https://scholar.google.com.hk/citations?user=UUbEzBYAAAAJ&hl=zh-CN

1. T Li, S Li, T Wu, Z Rao, S Tang, L Ji, Mao Ye*.(2026)  Illumination-Aware Visible Generative Flows for Thermal Pedestrian Detection,  IEEE Transactions on Multimedia

2. Luo, D., Xiang, Y., Wang, H., Ji, L., Li, S., & Ye Mao*. (2026). Deformable Feature Alignment and Refinement for moving infrared small target detection. Pattern Recognition, 169, 111894.

3. Nianxin Li, Mao Ye*, Lihua Zhou, Shuaifeng Li, Song Tang, Luping Ji, Ce Zhu,Multimodal Causal Reasoning for UAV Object Detection,Advances in Neural Information Processing Systems 38 (NeurIPS 2025)

4. T Li, S Li, S Li, X Qin, M Zhao, L Ji, Mao Ye*, (2025), SAM-Guided Semantic Knowledge Fusion for Visible-Infrared Object Detection, Proceedings of the 33rd ACM International Conference on Multimedia, 8835-8844

5. Zhou, L., Ye, Mao*, Li, N., Tang, S., Fan, X. Q., Deng, L., ... & Zhu, X. (2025). From Point to Flow: Enhancing Unsupervised Domain Adaptation with Flow Classification. IEEE Transactions on Circuits and Systems for Video Technology.

6. Zou, Z., Ye, Mao*, Ji, L., Zhou, L., Tang, S., Gan, Y., & Li, S. (2025). Long-Short Match for Lost Control in UAV Multi-Object Tracking. IEEE Transactions on Multimedia, 28, 786-800.

7. Luo, D., Xiang, Y., Wang, H., Ji, L., & Ye, Mao*. (2025). Knowledge adaptation for cross-domain moving infrared small target detection. IEEE Transactions on Geoscience and Remote Sensing.

8. Yue, J., Ye Mao*, Ji, L., Guo, H., & Zhu, C. (2025). A Survey of Deep-Learning-Based Compressed Video Quality Enhancement. IEEE Transactions on Broadcasting.

9. Li, N., Ye, Mao*, Zhou, L., Tang, S., Gan, Y., Liang, Z., & Zhu, X. (2025, April). Self-Prompting Analogical Reasoning for UAV Object Detection. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 39, No. 17, pp. 18412-18420).

10. Li, T., Li, S., Li, S., Qin, X., Zhao, M., Ji, L., & Ye, Mao*. (2025, October). SAM-Guided Semantic Knowledge Fusion for Visible-Infrared Object Detection. In Proceedings of the 33rd ACM International Conference on Multimedia (pp. 8835-8844).

11. Gan, Y., Yang, C., Ye Mao*, Huang, R., & Ouyang, D. (2025). Generative adversarial networks with learnable auxiliary module for image synthesis. ACM Transactions on Multimedia Computing, Communications and Applications, 21(4), 1-21.

12. Song Tang, Wenxin Su, Yan Gan, Mao Ye*, Jianwei Dr. Zhang, Xiatian Zhu*, (2025, Proxy Denoising for Source-Free Domain Adaptation, ICLR2025 ORAL (1.8%)

13. Li, S., Ye, Mao*, Zhou, L., Li, N., Xiao, S., Tang, S., & Zhu, X. (2024). Cloud object detector adaptation by integrating different source knowledge. Advances in Neural Information Processing Systems, 37, 25251-25283.

14. Zhao, Y., Ye, Mao*, Ji, L., Guo, H., & Zhu, C. (2024). Temporal adaptive learned surveillance video compression. IEEE Transactions on Broadcasting.

15. Chen, L., Ye, Mao*, Ji, L., Li, S., & Guo, H. (2024). Multi-reference-based cross-scale feature fusion for compressed video super resolution. IEEE Transactions on Broadcasting, 70(3), 895-908.

16. Li, S., Ye, Mao*, Ji, L., Tang, S., Gan, Y., & Zhu, X. (2024). Illumination distribution-aware thermal pedestrian detection. IEEE Transactions on Intelligent Transportation Systems.

17. Zou, Z., Ye, Mao*, Li, X., Ji, L., & Zhu, C. (2024). Stable Viewport-Based Unsupervised Compressed 360° Video Quality Enhancement. IEEE Transactions on Broadcasting, 70(2), 607-619.

18. Tang, S., Chang, A., Zhang, F., Zhu, X., Ye, Mao*, & Zhang, C. (2024). Source-free domain adaptation via target prediction distribution searching. International journal of computer vision, 132(3), 654-672.

19. Zhou, L., Li, N., Ye, Mao*, Zhu, X., & Tang, S. (2024). Source-free domain adaptation with class prototype discovery. Pattern recognition, 145, 109974.

20. Xiao, S., Ye, Mao*, He, Q., Li, S., Tang, S., & Zhu, X. (2024, October). Adversarial experts model for black-box domain adaptation. In Proceedings of the 32nd ACM International Conference on Multimedia (pp. 8982-8991).

21. Wang, H., Ye, Mao*, Zhu, X., Li, S., Li, X., & Zhu, C. (2023). Compressed-SDR to HDR video reconstruction. IEEE transactions on pattern analysis and machine intelligence, 46(5), 3679-3691.

22. Zhao, Y., Luo, D., Wang, F., Gao, H., Ye, Mao*, & Zhu, C. (2023). End-to-end compression for surveillance video with unsupervised foreground-background separation. IEEE Transactions on Broadcasting, 69(4), 966-978.

23. Zhou, L., Xiao, S., Ye, Mao*, Zhu, X., & Li, S. (2023). Adaptive mutual learning for unsupervised domain adaptation. IEEE Transactions on Circuits and Systems for Video Technology, 33(11), 6622-6634.

24. Zou, Z., Ye, Mao*, Li, S., Li, X., & Dufaux, F. (2023). 360° image saliency prediction by embedding self-supervised proxy task. IEEE Transactions on Broadcasting, 69(3), 704-714.

25. Gao, H., Cui, J., Ye, Mao*, Li, S., Zhao, Y., & Zhu, X. (2022, October). Structure-preserving motion estimation for learned video compression. In Proceedings of the 30th ACM international conference on multimedia (pp. 3055-3063).

26. Zhou, L., Ye, Mao*, Zhu, X., Li, S., & Liu, Y. (2022, October). Class discriminative adversarial learning for unsupervised domain adaptation. In Proceedings of the 30th ACM international conference on multimedia (pp. 4318-4326).

27. Luo, D., Ye, Mao*, Li, S., Zhu, C., & Li, X. (2022). Spatio-temporal detail information retrieval for compressed video quality enhancement. IEEE Transactions on Multimedia, 25, 6808-6820.

28. Peng, L., Hamdulla, A., Ye, Mao*, Li, S., Wang, Z., & Li, X. (2022). OVQE: Omniscient network for compressed video quality enhancement. IEEE Transactions on Broadcasting, 69(1), 153-164.

29. Xiong, L., Ye, Mao*, Zhang, D., Gan, Y., & Liu, Y. (2022). Source data-free domain adaptation for a faster R-CNN. Pattern Recognition, 124, 108436.

30. Zhang, D., Ye, Mao*, Liu, Y., Xiong, L., & Zhou, L. (2022). Multi-source unsupervised domain adaptation for object detection. Information Fusion, 78, 138-148.

31. Wang, Z., Ye, Mao*, Zhu, X., Peng, L., Tian, L., & Zhu, Y. (2022). Metateacher: Coordinating multi-model domain adaptation for medical image classification. Advances in Neural Information Processing Systems, 35, 20823-20837.

32. Li, S., Ye, Mao*, Zhu, X., Zhou, L., & Xiong, L. (2022). Source-free object detection by learning to overlook domain style. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 8014-8023).

33. Zhou, L., Ye, Mao*, Zhang, D., Zhu, C., & Ji, L. (2021). Prototype-based multisource domain adaptation. IEEE Transactions on Neural Networks and Learning Systems, 33(10), 5308-5320.

34. Zhang, F., Zhu, X., Dai, H., Ye, Mao*, & Zhu, C. (2020). Distribution-aware coordinate representation for human pose estimation. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 7093-7102).

35. Li, X., Ye, Mao*, Liu, Y., & Zhu, C. (2019). Adaptive deep convolutional neural networks for scene-specific object detection. IEEE Transactions on Circuits and Systems for Video Technology, 29(9), 2538-2551.

36. Zhang, F., Zhu, X., & Ye, Mao*. (2019). Fast human pose estimation. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 3517-3526).


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