Ming-Ming Cheng

Ming-Ming Cheng is a professor at the College of Computer ScienceNankai University, leading the Media Computing Lab. He received his Ph.D. from Tsinghua University in 2012 and then worked with Prof. Philip Torr in Oxford for two years. His research interests include computer vision and computer graphics. He has published over 100 papers in leading journals and conferences, such as IEEE TPAMI, ACM TOG, IEEE CVPR, etc. Many of his algorithms have become quite popular in the community, receiving more than 40,000+ paper citations. He received several research awards, including the National Science Foundation for Distinguished Young Scholars of China, the ACM China Rising Star Award, the IBM Global SUR award, etc. He is a senior member of the IEEE and on the editorial boards of the IEEE TPAMI and IEEE TIP. [CV]

程明明,南开大学杰出教授,计算机系主任。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30余篇),h-index为80,论文谷歌引用4万余次,单篇最高引用4700余次,多次入选全球高被引科学家中国高被引学者。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3名博士生获得省部级优秀博士论文奖。现担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 are mainly in 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) similar scene elements analysis for smart image manipulation. These works tried to recover parts of scene object-level information from images according to biological inspiration or with the help of 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 automatic extraction of full 3D information, categories 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: DBLPGoogleScopus, arXivPublons. 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 | bibproject | 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 ]

My Colleagues

Ju-Feng Yang
Professor
国家级四青人才
Chongyi Li
Professor
国家级四青人才
Deng-Ping Fan
Professor
国家级四青人才
Bo Ren
Assoc. Prof.
南开百青
Qibin Hou
Assoc. Prof.
南开百青
Xialei Liu
Assoc. Prof.
南开百青
Yaxing Wang
Assoc. Prof.
南开百青
Li Xiang
Assoc. Prof.
南开百青
Chun-Le Guo
Assoc. Prof.

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 are collaborating with leading scientists and researchers worldwide, with whom many highly influential pieces of research have been made possible. We encourage faculties 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

Major Honors & Awards

  • 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

Ph.D. Students

Master Students

Alumni

Deng-Ping Fan
Prof. @ Nankai
国家级四青人才
Ph.D. 2015–2019
Qibin Hou
Assoc. Prof @ Nankai
中科协青托
Ph.D. 2016–2019
Yun Liu
Researcher@ASTAR
Ph.D. 2016–2020
Shanghua Gao
Postdoc @ Harvard
Ph.D. 2018-2023
Yu-Huan Wu
Researcher @ ASTAR
Ph.D. 2018-2022
Jie Mei
Post-doc @ HNU
博新计划A档
Ph.D. 2019-2022
Jiang-Jiang Liu
Baidu
Ph.D. 2017-2022
Peng-Tao Jiang
OPPO
Ph.D. 2017-2022
Kai Zhao
Post-doc@UCLA
Ph.D. 2017-2020
Gang Xu
PostDoc @ CityU HK
Ph.D. 2018-2023
Jia-Xing Zhao
阿里星 @ Alibaba
M.Sc. 2017–2020
Jia-Wang Bian
Post-doc @ Oxford
B.Sc. 2012–2016
Shi-Jie Li
Ph.D. @ Bonn
M.Sc. 2016–2019
Yu-Chao Gu
Ph.D. @ NUS
M.Sc. 2019–2022
Zhao Zhang
SenseTime
M.Sc. 2019–2022
Qi Han
Megvii
M.Sc. 2018–2021
Chang-Bin Zhang
Ph.D. @ HKU
M.Sc. 2018–2021
Xiao-Wei Hu
ByteDance
M.Sc. 2016–2019
Jingyi Xu
Ph.D. @ Stony Brook
B.Sc. 2015–2019
Lin-Zhuo Chen
RA @ Zhejiang U.
M.Sc. 2018–2021
Rong Wang
中电科54所
M.Sc. 2016–2019
Yang Cao
Ph.D. @ HKUST
M.Sc. 2017–2020

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Wanglele

程老师, 您好,我最近在做视频显著性检测的相关工作,发现您的网址:https://mmcheng.net/davsod/,对视频显著性做了详细的解释,但是网址上相关的图片都失效了,无法显示,能否给我分享下相关的图片和视频呢?(wjx514051264@126.com)

Last edited 1 year ago by Wanglele

[…] Zheng Lin , Zheng-Peng Duan, Zhao Zhang , Chun-Le Guo, Ming-Ming Cheng, […]

Song-nuist

程老师您好!读了您2015年的《Global Contrast Based Salient Region Detection》,请问下在哪可以找到相关程序代码呢?如果您方便可否麻烦您发至我的邮箱,或者提供下载地址呢?

海天1度

程老师您好!想要请教一些关于Video Salient Object Detection (VSOD)以及Eye Fixation Prediction(EFP)的问题。(若有什么理解或表达错误的地方,恳请老师指正。)
(1)我看到一些采用半监督方法做VSOD的工作,但是,目前没有调研到采用半监督方法做EFP的工作,请问采用半监督做EFP,是不是有什么不合理的地方,或者是有哪些难点目前没办法解决?
(2)在DAVSOD数据集中,我发现少数fixation_map中标注的点,并不在GT_object标注的那个轮廓线内,所以,我就在想,对于Video Salient Object和Eye Fixation,人眼所关注的东西,是不是有些差别?还是说忽略了些什么东西?

祝好!

杜丽娜(Dulina@emails.bjut.edu.cn)

LEE

老师您好,看了2019的cpfp后想索要一份该模型在SIP数据集下的结果图片集,不知道能不能分享一下。

Hua Lee

老师您好,看完您发表的文章《Structure-Preserving Neural Style Transfer》后,我有一些疑问,希望老师在繁忙工作之余,帮我解惑一下,万分感谢。
1,训练的时,生成网络的输入只有X_content, 是不是每次训练后的网络只能生成特特定style的图片。
2,训练时将style的图片和content的图片同时输入到网络中,会不会使网络有更好的拓展性。

王华珂

程老师,您的网课《论文写作指导》链接失效,可否更新一下链接?

吕朝晖

程老师,请问2021 CVPR 还会有 Learning from Imperfect Data Challenge and Workshop 吗?

研二宣树星

程老师,您好,我看到您网站的一篇2020eccv的工作,Gradient-Induced Co-Saliency Detection,我看到这篇文章提出的拼图训练策略想实现一下,但不是很理解,发现提供的代码没有train部分,可以分享一下嘛

Zhao Zhang

您好,已经发送给您。

Liang

老师您好,我是澳门大学的研究生,想在您的基础上继续研究Semantic Edge Detection算法,我承诺不将代码或基于您的代码的研究成果商用,请问可以发我一份Semantic Edge Detection with Diverse Deep Supervision训练代码嘛?

Yun Liu

您好,因为这篇论文仍然在审稿状态(两年了),所以现阶段不方便共享代码。一旦论文被接收,我们一定第一时间开源代码。

xuqing

程老师您好,有幸拜读了您主页publications里展示的2020PAMI弱监督实例分割论文《Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance Segmentation》,所取得的结果令人印象深刻,请问您能否繁忙的工作之余,分享一下实验所用的代码,十分感激!!!

留意到github上在1年前已经有这篇文章的项目,但是目前只有Code is coming soon…

uclin

老师您好,有幸拜读了您发表的文章《Structure-Preserving Neural Style Transfer》,对其应用在所取得的结果令人印象深刻,请问您能否繁忙的工作之余,分享一下在实验所用的代码,十分感激!!!