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 Wenguan Wang sits on this spectrum.
This scientist: 238 publications — 59th percentile
59% 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 Wenguan Wang sits on this spectrum.
This scientist: 73 D-Index — 89th percentile
89% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Wenguan Wang is affiliated with the University of Technology Sydney in Australia. Their primary research domain is computer science, with a specialized focus on computer vision and pattern recognition. Wang's work spans several interconnected subfields including artificial intelligence, computational mechanics, environmental engineering, and geology.
The scientist has contributed extensively to the study and application of multimodal machine learning, advanced neural networks, domain adaptation, and few-shot learning. Key research topics in their portfolio also include advanced image and video retrieval techniques, human pose and action recognition, visual attention and saliency detection, as well as video surveillance and tracking methods.
Their recent publications indicate a concentration on semantic segmentation and object detection using deep learning approaches. Notable papers include:
Frequent collaborators with Wang include Yi Yang, Tianfei Zhou, Luc Van Gool, Liulei Li, and Jianbing Shen.
Their research outputs are often published in leading venues such as:
Wang's scholarly contributions are documented in over 300 publications, with a dominant presence in computer vision and pattern recognition comprising over two hundred entries. Their work is grounded in both theoretical and practical aspects of advanced neural networks and multimodal integration techniques.
Wenguan Wang;Qiuxia Lai;Huazhu Fu;Jianbing Shen
Wenguan Wang;Jianbing Shen
Wenguan Wang;Qiuxia Lai;Huazhu Fu;Jianbing Shen
Wenguan Wang;Jianbing Shen;Ling Shao
Wenguan Wang;Jianbing Shen;Fatih Porikli
Siyuan Qi;Wenguan Wang;Baoxiong Jia;Jianbing Shen
Wenguan Wang;Shuyang Zhao;Jianbing Shen;Steven C. H. Hoi
Xiankai Lu;Wenguan Wang;Chao Ma;Jianbing Shen
Wenguan Wang;Tianfei Zhou;Fisher Yu;Jifeng Dai
Wenguan Wang;Tianfei Zhou;Fisher Yu;Jifeng Dai
Deng-Ping Fan;Wenguan Wang;Ming-Ming Cheng;Jianbing Shen
Hongmei Song;Wenguan Wang;Sanyuan Zhao;Jianbing Shen
Wenguan Wang;Jianbing Shen;Ruigang Yang;Fatih Porikli
Unknown
Wenguan Wang;Jianbing Shen;Ling Shao
Jianbing Shen;Xiaopeng Hao;Zhiyuan Liang;Yu Liu
Hao-Shu Fang;Yuanlu Xu;Wenguan Wang;Xiaobai Liu
Jianbing Shen;Yunfan Du;Wenguan Wang;Xuelong Li
Unknown
Wenguan Wang;Jianbing Shen;Haibin Ling
Guolei Sun;Wenguan Wang;Jifeng Dai;Jifeng Dai;Luc Van Gool
Wenguan Wang;Xiankai Lu;Jianbing Shen;David Crandall
Xingping Dong;Jianbing Shen;Dajiang Yu;Wenguan Wang
Wenguan Wang;Yuanlu Xu;Jianbing Shen;Song-Chun Zhu
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