Antonio Torralba: h-index, Total Citations, and Citation Map
Antonio Torralba's h-index is 162 (355 i10-index, 172,914+ total citations across 649+ publications) according to Google Scholar as of July 2026. Antonio Torralba is affiliated with Professor of Computer Science, MIT.
Antonio Torralba is a researcher affiliated with Professor of Computer Science, MIT, specializing in various fields. Their work has been cited 172,914 times. This profile visualizes their global influence, spanning a global audience.
Antonio Torralba's Citation Metrics
Bibliometric impact based on 649 indexed publications.
- H-Index
- 162
- i10-Index
- 355
- Total Citations
- 172,914
- Citing Countries
- 0
As of July 2026.
Antonio Torralba has an h-index of 162 and 172,914 total citations across 649 publications, with research cited by institutions in 0 countries.
Download Exports (PNG, CSV, Poster)
Free Viewing Antonio Torralba's citation map is always free. Pay once to download poster, PNG, and CSV files for offline use or your visa packet.
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.
Learning deep features for discriminative localization
201615,248
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 Antonio Torralba's research
Antonio Torralba is a researcher at Professor of Computer Science, MIT. Their work has been cited 172,914 times across 649 publications (h-index 162), according to Google Scholar.
Their most-cited work, “Learning deep features for discriminative localization” (2016), has accumulated 15,248 citations. Other influential works include “Modeling the shape of the scene: A holistic representation of the spatial envelope” (2001) with 8,673 citations and “Places: A 10 million image database for scene recognition” (2017) with 6,266 citations.
