The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Ming-Ming Cheng sits on this spectrum.
This scientist: 209 publications — 49th percentile
49% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Ming-Ming Cheng sits on this spectrum.
This scientist: 93 D-Index — 97th percentile
97% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Ming-Ming Cheng is affiliated with Nankai University in China and has contributed extensively to the field of computer science, with a focus on computer vision and pattern recognition. Their research spans multiple subfields including artificial intelligence, media technology, radiology and imaging, as well as aerospace engineering.
The scientist's work covers a range of main topics, such as advanced neural network applications, domain adaptation and few-shot learning, advanced image and video retrieval techniques, visual attention and saliency detection, multimodal machine learning applications, advanced vision and imaging, and advanced image processing techniques.
Recent notable publications include:
Ming-Ming Cheng collaborates frequently with a group of co-authors, including Qibin Hou, Yun Liu, Deng-Ping Fan, Shanghua Gao, and Xialei Liu. These collaborations have contributed to a substantial body of work in the computer vision domain.
The scientist has a strong presence in several publication venues. The most frequent among these are:
Ming-Ming Cheng's academic output primarily focuses on advancing the understanding and application of neural networks and visual attention mechanisms in computer vision tasks. Their research contributions provide insights into localization, salient object detection, and multimodal learning, addressing challenges across multiple imaging and computational modalities.
Ming-Ming Cheng;Guo-Xin Zhang;Niloy J. Mitra;Xiaolei Huang
Sam Hare;Stuart Golodetz;Amir Saffari;Vibhav Vineet
Shang-Hua Gao;Ming-Ming Cheng;Kai Zhao;Xin-Yu Zhang
Ali Borji;Ming-Ming Cheng;Huaizu Jiang;Jia Li
Deng-Ping Fan;Ming-Ming Cheng;Yun Liu;Tao Li
Deng-Ping Fan;Cheng Gong;Yang Cao;Bo Ren
Qibin Hou;Ming-Ming Cheng;Xiaowei Hu;Ali Borji
Huaizu Jiang;Jingdong Wang;Zejian Yuan;Yang Wu
Ming-Ming Cheng;Ziming Zhang;Wen-Yan Lin;Philip Torr
Qibin Hou;Ming-Ming Cheng;Xiaowei Hu;Ali Borji
Ali Borji;Ming Ming Cheng;Qibin Hou;Huaizu Jiang
Jiaxing Zhao;Jiang-Jiang Liu;Deng-Ping Fan;Yang Cao
Unknown
Jiang-Jiang Liu;Qibin Hou;Ming-Ming Cheng;Jiashi Feng
Ming-Ming Cheng;Deng-Ping Fan
Yunchao Wei;Jiashi Feng;Xiaodan Liang;Ming-Ming Cheng
Yun Liu;Ming-Ming Cheng;Xiaowei Hu;Jia-Wang Bian
Tao Chen;Ming-Ming Cheng;Ping Tan;Ariel Shamir
Unknown
Deng-Ping Fan;Ge-Peng Ji;Guolei Sun;Ming-Ming Cheng
Peng-Tao Jiang;Chang-Bin Zhang;Qibin Hou;Ming-Ming Cheng
Ming-Ming Cheng;Jonathan Warrell;Wen-Yan Lin;Shuai Zheng
Jingdong Wang;Huaizu Jiang;Zejian Yuan;Ming-Ming Cheng
Ming Ming Cheng;Yun Liu;Wen Yan Lin;Ziming Zhang
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