Xiaogang Wang: h-index, Total Citations, and Citation Map
Xiaogang Wang's h-index is 154 (265 i10-index, 146,568+ total citations across 3+ publications) according to Google Scholar as of May 2026. Xiaogang Wang is affiliated with Professor of Electronic Engineering, the Chinese University of Hong Kong.
Xiaogang Wang is a researcher affiliated with Professor of Electronic Engineering, the Chinese University of Hong Kong, specializing in Computer vision, pattern recognition, machine learning. Their work has been cited 146,568 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Xiaogang Wang's Citation Metrics
Bibliometric impact based on 3 indexed publications.
- H-Index
- 154
- i10-Index
- 265
- Total Citations
- 146,568
- Citing Countries
- 10
As of May 2026.
Xiaogang Wang has an h-index of 154 and 146,568 total citations across 3 publications, with research cited by institutions in 10 countries.
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We've mapped 5,000 of 146,568 citations for Xiaogang Wang
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Global Impact Map
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Top Cited Works
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Pyramid Scene Parsing Network
201720,387
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
1 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher advanced deep learning methods for analyzing facial attributes in uncontrolled, real-world environments, establishing a foundational benchmark for robust feature extraction.
The researcher developed the Pyramid Scene Parsing Network, a seminal architecture for scene parsing that has garnered over 20,000 citations, establishing a foundational approach in computer vision.
The researcher introduced a residual attention network for image classification, a highly cited framework that appears to have significantly influenced subsequent computer vision research.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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