Abhinav Dhall

5.8k total citations · 1 hit paper
102 papers, 3.5k citations indexed

About

Abhinav Dhall is a scholar working on Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Cognitive Neuroscience. According to data from OpenAlex, Abhinav Dhall has authored 102 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Computer Vision and Pattern Recognition, 49 papers in Experimental and Cognitive Psychology and 20 papers in Cognitive Neuroscience. Recurrent topics in Abhinav Dhall's work include Emotion and Mood Recognition (48 papers), Human Pose and Action Recognition (24 papers) and Face and Expression Recognition (23 papers). Abhinav Dhall is often cited by papers focused on Emotion and Mood Recognition (48 papers), Human Pose and Action Recognition (24 papers) and Face and Expression Recognition (23 papers). Abhinav Dhall collaborates with scholars based in Australia, India and United States. Abhinav Dhall's co-authors include Roland Goecke, Tom Gedeon, Jyoti Joshi, Simon Lucey, Karan Sikka, Shreya Ghosh, Subrahmanyam Murala, Akshay Asthana, Jesse Hoey and Michael Wagner and has published in prestigious 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.

In The Last Decade

Abhinav Dhall

92 papers receiving 3.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Collecting Large, Richly Annotated Facial-Expression Databases from Movies

2012 459 citations Abhinav Dhall, Roland Goecke et al. IEEE Multimedia profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Abhinav Dhall Australia	29	2.4k	2.3k	597	498	386	102	3.5k
Shangfei Wang China	26	1.4k 0.6×	1.7k 0.7×	466 0.8×	435 0.9×	362 0.9×	141	2.6k
Gwen Littlewort United States	23	2.2k 0.9×	2.1k 0.9×	462 0.8×	881 1.8×	346 0.9×	38	3.6k
Ian Fasel United States	19	1.7k 0.7×	1.9k 0.8×	453 0.8×	505 1.0×	359 0.9×	42	3.0k
Zhihong Zeng China	20	1.8k 0.8×	1.3k 0.6×	507 0.8×	459 0.9×	502 1.3×	82	3.1k
Patrick Lucey United States	23	2.6k 1.1×	3.3k 1.4×	621 1.0×	577 1.2×	622 1.6×	71	4.7k
Jason Saragih United States	24	2.4k 1.0×	4.8k 2.1×	430 0.7×	531 1.1×	517 1.3×	59	5.9k
Zara Ambadar United States	19	3.1k 1.3×	2.9k 1.2×	394 0.7×	1.1k 2.3×	314 0.8×	24	4.6k
Irene Kotsia United Kingdom	20	1.4k 0.6×	2.5k 1.1×	567 0.9×	293 0.6×	834 2.2×	43	3.5k
Roland Goecke Australia	37	3.0k 1.3×	2.5k 1.1×	899 1.5×	786 1.6×	700 1.8×	173	4.9k
Jiro Gyoba Japan	21	1.5k 0.6×	1.5k 0.6×	342 0.6×	1.2k 2.3×	226 0.6×	122	3.1k

Countries citing papers authored by Abhinav Dhall

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Gupta, Parul, et al.. (2025). LayLens: Improving Deepfake Understanding through Simplified Explanations. 788–790.

2.

Dhall, Abhinav, et al.. (2025). A Survey on Deep Learning for Group-Level Emotion Recognition. IEEE Transactions on Computational Social Systems. 1–26.

3.

Subramanian, Ramanathan, et al.. (2025). Multiview Attention Fusion for Explainable Body Language Behavior Recognition. IEEE Transactions on Affective Computing. 16(3). 1984–1995. 1 indexed citations

4.

Dhall, Abhinav, et al.. (2024). ClipSwap: Towards High Fidelity Face Swapping via Attributes and CLIP-Informed Loss. 1–10. 1 indexed citations

5.

Ghosh, Shreya, et al.. (2024). AV-Deepfake1M: A Large-Scale LLM-Driven Audio-Visual Deepfake Dataset. Monash University Research Portal (Monash University). 7414–7423. 12 indexed citations

6.

Wong, KokSheik, et al.. (2024). Histohdr-Net: Histogram Equalization for Single LDR to HDR Image Translation. 2730–2736. 1 indexed citations

7.

Al-Shargie, Fares, et al.. (2024). Discrimination of Real and Deep Fake Videos using EEG Signals. PubMed. 2024. 1–4.

8.

Tariq, Usman, et al.. (2024). Real, Fake and Synthetic Faces - Does the Coin Have Three Sides?. 1–10. 2 indexed citations

9.

Dhall, Abhinav, et al.. (2023). EmotiW 2023: Emotion Recognition in the Wild Challenge. UNSWorks (University of New South Wales, Sydney, Australia). 746–749. 6 indexed citations

10.

Dhall, Abhinav, et al.. (2023). Do I Have Your Attention: A Large Scale Engagement Prediction Dataset and Baselines. 174–182. 12 indexed citations

11.

Tariq, Usman, et al.. (2023). Exploring Neurophysiological Responses to Cross-Cultural Deepfake Videos. 41–45. 4 indexed citations

12.

Huang, Xiaohua, Abhinav Dhall, Roland Goecke, Matti Pietikäinen, & Guoying Zhao. (2019). Analyzing Group-Level Emotion with Global Alignment Kernel based Approach. IEEE Transactions on Affective Computing. 13(2). 713–728. 7 indexed citations

13.

Ghosh, Shreya, Abhinav Dhall, Nicu Sebe, & Tom Gedeon. (2019). Predicting Group Cohesiveness in Images. Institutional Research Information System (Università degli Studi di Trento). 18 indexed citations

14.

Huang, Xiaohua, Abhinav Dhall, Roland Goecke, Matti Pietikäinen, & Guoying Zhao. (2018). Multimodal Framework for Analyzing the Affect of a Group of People. IEEE Transactions on Multimedia. 20(10). 2706–2721. 23 indexed citations

15.

Kaur, Amanjot, et al.. (2018). Prediction and Localization of Student Engagement in the Wild. 1–8. 80 indexed citations

16.

Dhall, Abhinav, Roland Goecke, Tom Gedeon, & Nicu Sebe. (2016). Emotion recognition in the wild. Journal on Multimodal User Interfaces. 10(2). 95–97. 12 indexed citations

17.

Sikka, Karan, Abhinav Dhall, & Marian Stewart Bartlett. (2014). Classification and weakly supervised pain localization using multiple segment representation. Image and Vision Computing. 32(10). 659–670. 44 indexed citations

18.

Joshi, Jyoti, Roland Goecke, Sharifa Alghowinem, et al.. (2013). Multimodal assistive technologies for depression diagnosis and monitoring. Journal on Multimodal User Interfaces. 7(3). 217–228. 131 indexed citations

19.

Dhall, Abhinav, Roland Goecke, Simon Lucey, & Tom Gedeon. (2012). Collecting Large, Richly Annotated Facial-Expression Databases from Movies. IEEE Multimedia. 19(3). 34–41. 459 indexed citations breakdown →

20.

Dhall, Abhinav, Roland Goecke, Simon Lucey, & Tom Gedeon. (2011). Static facial expression analysis in tough conditions: Data, evaluation protocol and benchmark. ANU Open Research (Australian National University). 2106–2112. 357 indexed citations

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.

Explore authors with similar magnitude of impact