Dong Liu Google Scholar: h-index, Total Citations, and Citation Map
Dong Liu's h-index is 64 (210 i10-index, 30,544+ total citations across 347+ publications) according to Google Scholar as of September 2026. Dong Liu is affiliated with University of Science and Technology of China.
Dong Liu is a researcher affiliated with University of Science and Technology of China, specializing in Image Compression, Video Coding, Image Processing. Their work has been cited 30,544 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Dong Liu's Citation Metrics
Bibliometric impact based on 347 indexed publications. Of these, 19 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 64
- i10-Index
- 210
- Total Citations
- 30,544
- Citing Countries
- 67
As of September 2026.
Dong Liu has an h-index of 64 and 30,544 total citations across 347 publications, with research cited by institutions in 67 countries.
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Global Impact Map
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Deep high-resolution representation learning for human pose estimation
20197,884
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.
1287 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered high-resolution representation learning for visual recognition, establishing a foundational framework for pixel-level labeling and region analysis that has been widely adopted across computer vision and medical imaging domains.
The researcher pioneered principled synthetic-to-real dehazing guided by physical priors, subsequently advancing the field with unpaired training methods leveraging Schrödinger bridges and diffusion models.
The researcher developed advanced CNN-based methods for hyperspectral recovery from RGB images, establishing a foundational approach for photon-efficient 3D imaging and spectral reconstruction.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Dong Liu's research
Dong Liu is a researcher in Image Compression, Video Coding and Image Processing at University of Science and Technology of China. Their work has been cited 30,544 times across 347 publications (h-index 64), according to Google Scholar.
Their most-cited work, “Deep high-resolution representation learning for human pose estimation” (2019), has accumulated 7,884 citations. Other influential works include “Deep high-resolution representation learning for visual recognition” (2020) with 6,415 citations and “High-Resolution Representations for Labeling Pixels and Regions” (2019) with 1,250 citations.
Citations of Dong Liu'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.
