Ming-Ming Cheng

Ming-Ming Cheng is a professor at Nankai University, the Executive Dean of the School of Excellent Engineers, and the academic leader of the media computing team. He received his Ph.D. from Tsinghua University in 2012 and then worked with Prof. Philip Torr in Oxford for two years. He has presided over projects including the National Science Fund for Distinguished Young Scholars, the National Science Fund for Excellent Young Scholars, and major project topics of the Ministry of Science and Technology of China. His main research directions cover artificial intelligence, computer vision, and computer graphics. He has published more than 100 academic papers in top-tier conferences/journals, including more than 40 in IEEE TPAMI. His h-index is 100, with more than 70,000 citations on Google Scholar. He has been selected as a Highly Cited Researcher (2022-2025) by Clarivate. His technical achievements have been applied to flagship products of multiple institutions, including Huawei and the National Disaster Reduction Center of China. He has won 2 first prizes in Natural Science awarded by the Ministry of Education of China and 2 other provincial- and ministerial-level science and technology awards. Four Ph.D. students supervised by him have won the provincial and ministerial-level Outstanding Doctoral Dissertation Award. Currently, he serves as the Director of the Tianjin Key Laboratory of Visual Computing and Intelligent Perception, Vice Chairman of the Tianjin Artificial Intelligence Society, and an editorial board member of top journals, including IEEE TPAMI, IEEE TIP, and Science China Information Sciences. [CV]

程明明，南开大学二级教授，卓越工程师学院执行院长，媒体计算团队学术带头人。主持承担了国家杰出青年科学基金、优秀青年科学基金项目、科技部重大项目课题等。他的主要研究方向是人工智能、计算机视觉和计算机图形学，在SCI一区/CCF A类刊物上发表学术论文100余篇（含IEEE TPAMI论文40余篇），h-index为100，论文谷歌引用7万余次，单篇最高引用5千余次，多次入选全球高被引科学家和中国高被引学者。技术成果被应用于华为、国家减灾中心等多个单位的旗舰产品。获得教育部自然科学一等奖2项、其他省部级科技奖2项。培养的4名博士生获得省部级优秀博士论文奖。现担任天津市视觉计算与智能感知重点实验室主任、中国图象图形学学会副秘书长、天津市人工智能学会副理事长和顶级期刊IEEE TPAMI, IEEE TIP和《中国科学：信息科学》编委。[简历]

招收博士、硕士研究生，来信前请务必阅读：关于研究生招生

Research

I’m currently working on image scene analysis, editing, and retrieval. These works primarily focus on the following aspects: (I) biologically motivated salient region detection and segmentation; (II) sketch-based image retrieval and composition; (III) interactive image analysis and manipulation; (IV) analysis of similar scene elements for smart image manipulation. These works attempted to recover parts of scene object-level information from images, drawing inspiration from biology or utilizing simple user assistance in sketch form. Such scene object-level information includes one or more parts of the following aspects: the object of interest regions, object correspondence, region layering, symmetry, repetition, and 3D relations. Ideally, we expect the automatic extraction of full 3D information, including category names, attributes, and object relations, about the underlying image scene for intelligent image understanding, manipulation, organization, and retrieval. [Research galleries]

Selected Publications

My publications can be found here. See also: DBLP, Google, Scopus, arXiv, Publons, WOS. Here are some recent publications.

  1. Large-scale Unsupervised Semantic Segmentation, Shanghua Gao, Zhong-Yu Li, Ming-Hsuan Yang, Ming-Ming Cheng*, Junwei Han, Philip Torr, IEEE TPAMI, 45(6):7457-7476, 2023. [pdf | code | bib | 中译版]
  2. A Highly Efficient Model to Study the Semantics of Salient Object Detection, Ming-Ming Cheng*#, Shanghua Gao#, Ali Borji, Yong-Qiang Tan, Zheng Lin, Meng Wang, IEEE TPAMI, 2022. [pdf | bib | project | code | 中译版]
  3. Structure-measure: A New Way to Evaluate Foreground Maps, Ming-Ming Cheng*, Deng-Ping Fan, IJCV,129(9):2622-2638, 2021. [pdf | code | bib |project | 中译版]
  4. Res2Net: A New Multi-scale Backbone Architecture, Shanghua Gao#, Ming-Ming Cheng*#, Kai Zhao, Xin-Yu Zhang, Ming-Hsuan Yang, Philip Torr, IEEE TPAMI, 43(2):652-662, 2021. [pdf | code | project |PPT | bib  | 中译版]
  5. Richer Convolutional Features for Edge Detection, Yun Liu, Ming-Ming Cheng*, Xiaowei Hu, Jia-Wang Bian, Le Zhang, Xiang Bai, Jinhui Tang, IEEE TPAMI, 41(8):1939-1946, 2019. [pdf|project|bib|code|中译版]
  6. Deeply supervised salient object detection with short connections, Qibin Hou, Ming-Ming Cheng*, Xiaowei Hu, Ali Borji, Zhuowen Tu, Philip Torr, IEEE TPAMI, 41(4):815-828, 2019.  [pdf|project|bib|code]
  7. Structure-Preserving Neural Style Transfer, Ming-Ming Cheng*#, Xiao-Chang Liu#, Jie Wang, Shao-Ping Lu, Yu-Kun Lai, Paul L. Rosin, IEEE TIP, 29:909-920, 2020. [pdf | bib | project | code]
  8. Shifting More Attention to Video Salient Object Detection, Deng-Ping Fan, Wenguan Wang, Ming-Ming Cheng*, Jianbing Shen, IEEE CVPR (Oral & Best Paper Finalist), 2019. [pdf|bib|中译版|code|project]
  9. 互联网图像驱动的语义分割自主学习, 侯淇彬, 韩凌昊, 刘姜江, 程明明*, 中国科学：信息科学, 2021. [pdf | bib | project]
  10. 认知规律启发的物体分割评价标准及损失函数，范登平, 季葛鹏, 秦雪彬, 程明明*, 中国科学：信息科学, 2021. [ pdf | code | bib ]

媒体计算实验室老师

丁丹
教授
国家级高层次人才
杨巨峰
教授
国家级四青人才
李重仪
教授
国家级四青人才
范登平
教授
国家级四青人才
刘云
教授
国家级四青人才
刘夏雷
教授
国家级四青人才
郭青
教授
国家级四青人才
孙国磊
教授
国家级四青人才
侯淇彬
副教授
国家级四青人才
任博
教授
南开百青
李翔
副教授
南开百青
郭春乐
副教授
南开百青
戴一冕
副教授
姜智卓
副教授
南开百青
黄川
副教授.
南开百青

We are looking forward to having elegant students or researchers join us. Positions for Master’s, Ph.D., and post-doc are opening. If you are interested in our research and want to join us, please send your CV (maximum 2 pages) and grades to cmm_AT_nankai.edu.cn.

Research Collaborators (partial)

We collaborate with leading scientists and researchers worldwide, with whom many highly influential pieces of research have been made possible. We encourage faculty and students to continue such collaborations by doing joint research and/or physically visiting these collaborators.

Shi-Min Hu
Tsinghua
中国科学院院士
Philip Torr
Oxford Univ.
Fellow of the Royal Society
Shui-Cheng Yan
NUS
IEEE/IAPR Fellow
Zhuo-Wen Tu
UCSD
Marr Prize winner
Ming-Hsuan Yang
UC Merced
IEEE Fellow
Paul Rosin
Cardiff Univ.
IAPR Fellow
Niloy Mitra
UCL
SIGGRAPH Award Winner

奖励与荣誉

  • 2025: 开放环境自适应视觉感知理论与方法，天津市自然科学奖一等奖，程明明, 侯淇彬, 胡清华, 汪萌, 王煜,高尚华, 刘云, 姜鹏涛
  • 2023: 视觉媒体的层次化内容感知，教育部自然科学一等奖，赵耀, 程明明, 魏云超, 侯淇彬, 韦世奎
  • 2020: 图像场景理解与内容敏感图像处理，吴文俊人工智能科学技术奖自然科学二等奖，程明明, 侯淇彬, 杨巨峰, 范登平, 刘云
  • 2019: 弱监督条件下的图像语义分割研究，中国图象图形学学会科学技术奖一等奖，赵耀，程明明，魏云超
  • 2019: 天津市中青年科技创新领军人才
  • 2019: 天津市青年科技奖
  • 2016年度国家“万人计划”青拔
  • 2016: ACM中国新星奖
  • 2015: 中科协青年人才托举计划
  • 2013: 北京市优秀博士论文奖
  • 2013: 可视媒体几何计算的理论与方法，教育部自然科学一等奖，胡事民、黄继武、艾海舟、陈韬、黄畅、程明明、来煜昆、毕宁、项世军

博士生

郑兆晖
李震
王家宝
靳鑫
朱子悦
李钟毓
张旭迎

硕士生

武睿祺
陈宇铭
周宇鹏
翟江天
段正鹏

历年毕业生

学制说明：本科直博默认5年学制，普博生默认4年，硕转博转后按照普博生重新计算。实验室到目前为止没有学生超过上述年限，大约20-30%的博士生提前毕业。

范登平
国家级”四青”
普博 2015–2019
侯淇彬
国家级”四青”
普博 2016–2019
刘云
国家级”四青”
直博 2016–2020
赵凯
上海大学副教授
普博 2017-2020
吴宇寰
新加坡AStar研究员
直博 2018-2022
梅杰
博新计划A档
普博 2019-2022
刘姜江
京东
转博 2017-2022
姜鹏涛
研究员@vivo
转博 2017-2022
高尚华
哈佛大学博后
转博 2018-2023
Gang Xu
光明实验室副研
直博 2018-2023
林铮
CCF CAD&CG优博
直博 2018-2023
李震
阿里
普博 2020-2024
郑兆晖
CCF-CV 新秀奖
普博 2021-2025
李钟毓
青云计划@腾讯
直博 2021-2026
张旭迎
TGT@京东
普博 2022-2026
边佳旺
南洋理工助理教授
本科 2012–2016
徐婧祎
Stony Brook
本科 2015–2019
李仕杰
Ph.D. @ Bonn
硕士 2016–2019
胡晓伟
字节跳动
硕士 2016–2019
赵嘉星
阿里星 @ 阿里
硕士 2017–2020
曹洋
Ph.D. @ HKUST
硕士 2017–2020
张长彬
Ph.D. @ HKU
硕士 2018–2021
陈林卓
Ph.D. @ NJU
硕士 2018–2021
韩琦
阶跃星辰
硕士 2018–2021
顾宇超
Nvidia@新加坡
硕士 2019–2022
张钊
AI先锋@商汤
硕士 2019–2022
翟江天
天演资本
硕士 2022–2025
杨雨奇
百度
硕士 2022–2025

学术服务

149 thoughts on “Ming-Ming Cheng”

  • 读到程明明教授的主页，想起他早期在显著性检测和图像分割上的工作确实影响了不少后来者，尤其是从清华到牛津再回南开的轨迹，看得出他对学术的专注和坚持。作为高校同行，很欣赏他把媒体计算团队带得有声有色，这种既做前沿研究又重视工程落地的风格，在当下浮躁的环境里不多见。

    说到科研项目管理，我平时会用PlanLiva来跟踪课题进度和团队协作，它帮我清晰梳理了多个并行项目的节点，减少了来回沟通的成本。程教授团队的方向虽然和我不同，但高效的组织方式对任何实验室来说都是宝贵的资产，希望以后有机会多交流这方面的经验。

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@ARTICLE{Gao22LUSS,
  author={Gao, Shanghua and Li, Zhong-Yu and Yang, Ming-Hsuan and Cheng, Ming-Ming and Han, Junwei and Torr, Philip},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
  title={Large-scale Unsupervised Semantic Segmentation}, 
  year={2023},
  volume={45},
  number={6},
  pages={7457-7476},
  doi={10.1109/TPAMI.2022.3218275}
}
No, thank you. I do not want.
100% secure your website.
Powered by 
@ARTICLE{21PAMI-Sal100K,
  author={Ming-Ming Cheng and Shang-Hua Gao and Ali Borji and Yong-Qiang Tan and Zheng Lin and Meng Wang},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
  title={A Highly Efficient Model to Study the Semantics of Salient Object Detection}, 
  year={2022},
  volume={44},
  number={11},
  pages={8006-8021},
  doi={10.1109/TPAMI.2021.3107956}
}
@inproceedings{GaoEccv20Sal100K,
  title={Highly Efficient Salient Object Detection with 100K Parameters},
  author={Shang-Hua Gao and Yong-Qiang Tan and Ming-Ming Cheng and Chengze Lu and Yunpeng Chen and Shuicheng Yan},
  booktitle = {European Conference on Computer Vision (ECCV)},
  pages = {702-721},
  doi = {10.1007/978-3-030-58539-6_42}, 
  year={2020},
}
@article{Cheng2021sMeasure,
  title={Structure-measure: A New Way to Evaluate Foreground Maps},
  author={Ming-Ming Cheng and Deng-Ping Fan},
  journal={International Journal of Computer Vision (IJCV)},
  year={2021},
  volume={129},
  number={9},
  pages={2622-2638},
  doi = {10.1007/s11263-021-01490-8},
}
Powered by 
@ARTICLE{pami21Res2net, 
  author={Shang-Hua Gao and Ming-Ming Cheng and Kai Zhao and Xin-Yu Zhang and Ming-Hsuan Yang and Philip Torr}, 
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
  title={Res2Net: A New Multi-scale Backbone Architecture}, 
  year={2021}, 
  volume={43}, 
  number={2}, 
  pages={652-662}, 
  doi={10.1109/TPAMI.2019.2938758}, 
}

 

@ARTICLE{TIP20_SP_NPR, 
	author={Ming-Ming Cheng and Xiao-Chang Liu and Jie Wang and Shao-Ping Lu and Yu-Kun Lai and Paul L. Rosin}, 
	journal={IEEE Transactions on Image Processing}, 
	title={Structure-Preserving Neural Style Transfer}, 
	year={2020}, 
	volume={29},  
	pages={909-920}, 
	doi={10.1109/TIP.2019.2936746}, 
}

 

@ARTICLE{21SC_WebSegE,
    author={侯淇彬 and 韩凌昊 and 刘姜江 and 程明明},
    journal={中国科学：信息科学}, 
    title={互联网图像驱动的语义分割自主学习}, 
    year={2021},
    volume={51},
    number={7},
    pages={1084-1099},
    doi={10.1360/SSI-2020-0146},
}

@ARTICLE{21SC_WebSeg,
    author={Qibin Hou and Linghao Han and Ming-Ming Cheng},
    journal={Sci Sin Inform}, 
    title={Autonomous Learning of Semantic Segmentation from Internet Images (in Chinese)}, 
    year={2021},
    volume={51},
    number={7},
    pages={1084-1099},
    doi={10.1360/SSI-2020-0146},
}

 

@article{21SC-EmeasureCN,
  author = {范登平 and 季葛鹏 and 秦雪彬 and 程明明},
  title = {认知规律启发的物体分割评价标准及损失函数},
  journal = {中国科学：信息科学},
  year = {2021},
  pages = {1475-1489},
  volume={51},
  number={9},
  doi = {https://doi.org/10.1360/SSI-2020-0370}
}

@article{21SC-Emeasure,
  author = {Dengping Fan and Gepeng Ji and Xuebin Qin and Ming-Ming Cheng},
  title = {Cognitive Vision Inspired Object Segmentation Metric and Loss Function},
  journal = {SCIENTIA SINICA Informationis},
  pages = {1475--1489},
  volume = {51},
  number = {9},
  doi = "https://doi.org/10.1360/SSI-2020-0370",
}