Yu-Gang Jiang Google Scholar: h-index, Total Citations, and Citation Map
Yu-Gang Jiang's h-index is 104 (368 i10-index, 43,767+ total citations across 641+ publications) according to Google Scholar as of October 2026. Yu-Gang Jiang is affiliated with Fudan University, IEEE & IAPR & CCF Fellow.
Yu-Gang Jiang is a researcher affiliated with Fudan University, IEEE & IAPR & CCF Fellow, specializing in Video Analysis, Multimodal AI, Embodied AI. Their work has been cited 43,767 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Yu-Gang Jiang's Citation Metrics
Bibliometric impact based on 641 indexed publications.
- H-Index
- 104
- i10-Index
- 368
- Total Citations
- 43,767
- Citing Countries
- 18
As of October 2026.
Yu-Gang Jiang has an h-index of 104 and 43,767 total citations across 641 publications, with research cited by institutions in 18 countries.
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Global Impact Map
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Pixel2mesh: Generating 3d mesh models from single rgb images
20181,982
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.
2 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed Pixel2Mesh, a seminal method for generating 3D mesh models from single RGB images, establishing a foundational approach in computer vision.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Yu-Gang Jiang's research
Yu-Gang Jiang is a researcher in Video Analysis, Multimodal AI and Embodied AI at Fudan University, IEEE & IAPR & CCF Fellow. Their work has been cited 43,767 times across 641 publications (h-index 104), according to Google Scholar.
Their most-cited work, “Pixel2mesh: Generating 3d mesh models from single rgb images” (2018), has accumulated 1,982 citations.
Citations of Yu-Gang Jiang's research come primarily from United States, China and Germany, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
