Abhinav Dhall
- Experimental and Cognitive Psychology top 0.5%
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 2%
- Cognitive Neuroscience top 5%
- Signal Processing top 2%
- Co-authors
- Roland GoeckeTom GedeonJyoti JoshiSimon LuceyKaran SikkaShreya GhoshSubrahmanyam MuralaAkshay Asthana
- Topics
- Emotion and Mood Recognition (48 papers)Human Pose and Action Recognition (24 papers)Face and Expression Recognition (23 papers)
- Cited by
- Experimental and Cognitive PsychologyComputer Vision and Pattern RecognitionHuman-Computer Interaction
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Visualization and Computer GraphicsIEEE Transactions on Instrumentation and Measurement
- Partner nations
- AustraliaIndiaUnited States
In The Last Decade
Abhinav Dhall
92 papers receiving 3.4k citations
Hit Papers
Peers
Comparison fields: 5 of 121
- Experimental and Cognitive Psychology 2.4k
- Computer Vision and Pattern Recognition 2.3k
- Artificial Intelligence 597
- Cognitive Neuroscience 498
- Signal Processing 386
Countries citing papers authored by Abhinav Dhall
This map shows the geographic impact of Abhinav Dhall's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Abhinav Dhall with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abhinav Dhall more than expected).
Fields of papers citing papers by Abhinav Dhall
This network shows the impact of papers produced by Abhinav Dhall. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Abhinav Dhall. The network helps show where Abhinav Dhall may publish in the future.
Co-authorship network of co-authors of Abhinav Dhall
This figure shows the co-authorship network connecting the top 25 collaborators of Abhinav Dhall. A scholar is included among the top collaborators of Abhinav Dhall based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Abhinav Dhall. Abhinav Dhall is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 12 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 2 | |
| 9 | 6 | |
| 10 | 12 | |
| 11 | 4 | |
| 12 | 7 | |
| 13 | 18 | |
| 14 | 23 | |
| 15 | 80 | |
| 16 | 12 | |
| 17 | 44 | |
| 18 | 131 | |
| 19 | Collecting Large, Richly Annotated Facial-Expression Databases from Moviesbreakdown → | 459 |
| 20 | 357 |
About Abhinav Dhall
Abhinav Dhall is a scholar working on Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 102 papers that have together received 3.5k indexed citations. Recurring topics across this work include Emotion and Mood Recognition (48 papers), Human Pose and Action Recognition (24 papers) and Face and Expression Recognition (23 papers). The work is most often cited by research in Experimental and Cognitive Psychology (2.4k citations), Computer Vision and Pattern Recognition (2.3k citations) and Human-Computer Interaction (241 citations). Abhinav Dhall has collaborated with scholars based in Australia, India and United States. Frequent co-authors include Roland Goecke, Tom Gedeon, Jyoti Joshi, Simon Lucey, Karan Sikka, Shreya Ghosh, Subrahmanyam Murala, Akshay Asthana, Jesse Hoey and Michael Wagner. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Visualization and Computer Graphics and IEEE Transactions on Instrumentation and Measurement.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.