Richard Zhang: h-index, Total Citations, and Citation Map
Richard Zhang's h-index is 45 (66 i10-index, 52,859+ total citations across 139+ publications) according to Google Scholar as of September 2026. Richard Zhang is affiliated with Principal Scientist, Adobe.
Richard Zhang is a researcher affiliated with Principal Scientist, Adobe, specializing in Computer Vision, Machine Learning, Deep Learning. Their work has been cited 52,859 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Richard Zhang's Citation Metrics
Bibliometric impact based on 139 indexed publications.
- H-Index
- 45
- i10-Index
- 66
- Total Citations
- 52,859
- Citing Countries
- 69
As of September 2026.
Richard Zhang has an h-index of 45 and 52,859 total citations across 139 publications, with research cited by institutions in 69 countries.
Global Impact Map
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The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
201821,432
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.
The researcher established deep neural network features as a robust perceptual metric for image quality, fundamentally shifting how visual similarity is quantified in computer vision.
The researcher advanced image colorization by publishing a seminal 2016 ECCV paper that has garnered over 5,000 citations, establishing a foundational approach in computer vision.
The researcher established a foundational framework for detecting CNN-generated images, demonstrating their initial detectability and highlighting the evolving nature of synthetic media identification challenges.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Richard Zhang's research
Richard Zhang is a researcher in Computer Vision, Machine Learning and Deep Learning at Principal Scientist, Adobe. Their work has been cited 52,859 times across 139 publications (h-index 45), according to Google Scholar.
Their most-cited work, “The Unreasonable Effectiveness of Deep Features as a Perceptual Metric” (2018), has accumulated 21,432 citations. Other influential works include “The Unreasonable Effectiveness of Deep Features as a Perceptual Metric” (2018) with 21,432 citations and “Colorful Image Colorization” (2016) with 5,076 citations.
Citations of Richard Zhang's research come primarily from China, United States and United Kingdom, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
