Dahua Lin: h-index, Total Citations, and Citation Map
Dahua Lin's h-index is 136 (398 i10-index, 99,432+ total citations across 581+ publications) according to Google Scholar as of July 2026. Dahua Lin is affiliated with The Chinese University of Hong Kong.
Dahua Lin is a researcher affiliated with The Chinese University of Hong Kong, specializing in computer vision, machine learning, probabilistic inference. Their work has been cited 99,432 times. This profile visualizes their global influence, spanning a global audience.
Dahua Lin's Citation Metrics
Bibliometric impact based on 581 indexed publications.
- H-Index
- 136
- i10-Index
- 398
- Total Citations
- 99,432
- Citing Countries
- 0
As of July 2026.
Dahua Lin has an h-index of 136 and 99,432 total citations across 581 publications, with research cited by institutions in 0 countries.
Download Exports (PNG, CSV, Poster)
Free Viewing Dahua Lin's citation map is always free. Pay once to download poster, PNG, and CSV files for offline use or your visa packet.
We've mapped 5,000 of 99,432 citations for Dahua Lin
We've shown the most-cited 5,000. Unlock the full crawl (94,432 more citations) to see every institution citing this scholar.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
Starting…
Pins will appear here as institutions are resolved — no need to refresh.
Spatial temporal graph convolutional networks for skeleton-based action recognition
20187,365
Top Citing Countries
Top Citing Institutions
No institution data available.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
Related Guides
Learn how to use citation maps for your research and visa applications.
About Dahua Lin's research
Dahua Lin is a researcher in computer vision, machine learning and probabilistic inference at The Chinese University of Hong Kong. Their work has been cited 99,432 times across 581 publications (h-index 136), according to Google Scholar.
Their most-cited work, “Spatial temporal graph convolutional networks for skeleton-based action recognition” (2018), has accumulated 7,365 citations. Other influential works include “Temporal segment networks: Towards good practices for deep action recognition” (2016) with 5,599 citations and “Unsupervised feature learning via non-parametric instance discrimination” (2018) with 5,468 citations.
