Trisha Mittal

495 total citations
12 papers, 231 citations indexed

About

Trisha Mittal is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Trisha Mittal has authored 12 papers receiving a total of 231 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 2 papers in Signal Processing. Recurrent topics in Trisha Mittal's work include Generative Adversarial Networks and Image Synthesis (4 papers), Human Pose and Action Recognition (3 papers) and Digital Media Forensic Detection (3 papers). Trisha Mittal is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (4 papers), Human Pose and Action Recognition (3 papers) and Digital Media Forensic Detection (3 papers). Trisha Mittal collaborates with scholars based in United States and India. Trisha Mittal's co-authors include Dinesh Manocha, Aniket Bera, Rohan Chandra, Uttaran Bhattacharya, Viswanathan Swaminathan, John Collomosse, Ritwik Sinha, Shiv Surya, R. Venkatesh Babu and Puneet Mathur and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and IEEE Multimedia.

In The Last Decade

Trisha Mittal

11 papers receiving 223 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Trisha Mittal United States	6	186	88	38	19	19	12	231
Claire-Hélène Demarty France	8	221 1.2×	120 1.4×	41 1.1×	18 0.9×	8 0.4×	31	262
Uttaran Bhattacharya United States	6	224 1.2×	85 1.0×	43 1.1×	16 0.8×	17 0.9×	15	275
Christos Tzelepis United Kingdom	9	162 0.9×	65 0.7×	29 0.8×	10 0.5×	6 0.3×	21	208
Brian Dolhansky United States	6	150 0.8×	73 0.8×	28 0.7×	6 0.3×	6 0.3×	8	211
Pavel Ircing Czechia	9	83 0.4×	215 2.4×	52 1.4×	11 0.6×	13 0.7×	41	295
Daniel Moreira Brazil	10	211 1.1×	97 1.1×	51 1.3×	21 1.1×	4 0.2×	22	290
Noa García Japan	9	200 1.1×	120 1.4×	13 0.3×	10 0.5×	11 0.6×	28	275
Byeongchang Kim South Korea	8	170 0.9×	225 2.6×	28 0.7×	6 0.3×	15 0.8×	15	348
Daiheng Gao China	6	172 0.9×	47 0.5×	17 0.4×	10 0.5×	4 0.2×	12	201

Countries citing papers authored by Trisha Mittal

Since Specialization

Citations

This map shows the geographic impact of Trisha Mittal'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 Trisha Mittal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Trisha Mittal more than expected).

Fields of papers citing papers by Trisha Mittal

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Trisha Mittal. 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 Trisha Mittal. The network helps show where Trisha Mittal may publish in the future.

Co-authorship network of co-authors of Trisha Mittal

This figure shows the co-authorship network connecting the top 25 collaborators of Trisha Mittal. A scholar is included among the top collaborators of Trisha Mittal 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 Trisha Mittal. Trisha Mittal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

1.

Mittal, Trisha, et al.. (2025). Analysis of Human Perception in Distinguishing Real and AI-Generated Faces: An Eye-Tracking Based Study. 1–10. 2 indexed citations

2.

Mittal, Trisha, et al.. (2024). S2MGen: A synthetic skin mask generator for improving segmentation. 1–8. 1 indexed citations

3.

Mittal, Trisha, et al.. (2024). Towards determining perceived audience intent for multimodal social media posts using the theory of reasoned action. Scientific Reports. 14(1). 10606–10606. 3 indexed citations

4.

Mittal, Trisha, et al.. (2023). Naturalistic Head Motion Generation from Speech. 1–5. 1 indexed citations

5.

Mittal, Trisha, Ritwik Sinha, Viswanathan Swaminathan, John Collomosse, & Dinesh Manocha. (2023). Video Manipulations Beyond Faces: A Dataset with Human-Machine Analysis. 643–652. 10 indexed citations

6.

Gupta, Vikram, et al.. (2022). 3MASSIV: Multilingual, Multimodal and Multi-Aspect dataset of Social Media Short Videos. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 21032–21043. 8 indexed citations

7.

Mittal, Trisha, Aniket Bera, & Dinesh Manocha. (2021). Multimodal and Context-Aware Emotion Perception Model With Multiplicative Fusion. IEEE Multimedia. 28(2). 67–75. 17 indexed citations

8.

Mittal, Trisha, et al.. (2021). BOhance: Bayesian Optimization for Content Enhancement. 2. 17–24.

9.

Mittal, Trisha, Uttaran Bhattacharya, Rohan Chandra, Aniket Bera, & Dinesh Manocha. (2020). Emotions Don't Lie. 2823–2832. 175 indexed citations

10.

Mittal, Trisha, Uttaran Bhattacharya, Rohan Chandra, Aniket Bera, & Dinesh Manocha. (2020). Emotions Don't Lie: A Deepfake Detection Method using Audio-Visual Affective Cues. 8 indexed citations

11.

Sarvadevabhatla, Ravi Kiran, Shiv Surya, Trisha Mittal, & R. Venkatesh Babu. (2018). Pictionary-Style Word Guessing on Hand-Drawn Object Sketches: Dataset, Analysis and Deep Network Models. IEEE Transactions on Pattern Analysis and Machine Intelligence. 42(1). 221–231. 5 indexed citations

12.

Mittal, Trisha, Prachi Gupta, & Shampa Chakraverty. (2014). Application of Rough Sets in diagnosis of the depressive state of mind. 3. 1–6. 1 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.

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