Xiaobo An

530 citations
14 papers · 390 · h-index 8

Impact in

Papers in

Xiaobo An

11 papers receiving 383 citations

Peers

Xiaobo An
Comparison fields: 5 of 48
  • Computer Graphics and Computer-Aided Design 85
  • Computer Vision and Pattern Recognition 324
  • Cognitive Neuroscience 82
  • Media Technology 26
  • Experimental and Cognitive Psychology 35
Replace L. Sharan with:
L. Sharan United States
Mohamed–Chaker Larabi France
Antoine Toisoul United Kingdom
Bastian Goldlücke Germany
Dimitris Samaras United States
Ondřej Drbohlav Czechia
Alexandre Chapiro United States
Robert Benavente Spain
Alan Chalmers United Kingdom
Anna Tomaszewska Poland
Xiaobo An relative to L. Sharan United States L. Sharan's profile →
Citations per field
00.5×3.9×
L. Sharan · 1×
Citations per year

Countries citing papers authored by Xiaobo An

Since Specialization
Citations

This map shows the geographic impact of Xiaobo An's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiaobo An with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaobo An more than expected).

Fields of papers citing papers by Xiaobo An

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaobo An. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiaobo An. The network helps show where Xiaobo An may publish in the future.

Co-authors

The 14 scholars most cited alongside Xiaobo An, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xiaobo An Line = papers co-authored together Xiaobo An links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2008174
2 201377
3 201051
4 201225
5 200819
6 201414
7 20118
8 20117
9 20116
10 20065
11 20143
12 20061
13 20150
14 20240

About Xiaobo An

Xiaobo An is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Cognitive Neuroscience, Computational Mechanics and Aerospace Engineering, having authored 14 papers that have together received 390 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (6 papers), Computer Graphics and Visualization Techniques (6 papers), Face Recognition and Perception (4 papers), 3D Shape Modeling and Analysis (4 papers), Face recognition and analysis (3 papers), Visual Attention and Saliency Detection (2 papers), Advanced Power Amplifier Design (1 paper) and Color Science and Applications (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (85 citations), Computer Vision and Pattern Recognition (324 citations), Cognitive Neuroscience (82 citations), Media Technology (26 citations) and Experimental and Cognitive Psychology (35 citations). Xiaobo An has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Fabio Pellacini, Alice J. O’Toole, P. Jonathon Phillips, Vaidehi Natu, Joseph Dunlop, Xin Tong, Guofeng Zhang, Hujun Bao, Xueying Qin and Wei Chen. Their work appears in journals such as ACM Transactions on Graphics, Image and Vision Computing, Psychological Science, NeuroImage and Computer Graphics Forum.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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