Uttaran Bhattacharya
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- Human Pose and Action Recognition 7
- Generative Adversarial Networks and Image Synthesis 2
- Advanced Image and Video Retrieval Techniques 2
- Multimodal Machine Learning Applications 2
- Human-Computer Interaction top 10%
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- Anomaly Detection Techniques and Applications 3
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- Human Motion and Animation 4
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- Emotion and Mood Recognition 3
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- Digital Transformation in Industry 2
- Co-authors
- Dinesh ManochaAniket BeraTrisha MittalRohan ChandraKyra KapsaskisTanmay RandhavaneKurt GrayViswanathan Swaminathan
- Journals
- arXiv (Cornell University) (1 paper)Proceedings of the 30th ACM International Conference on Multimedia (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (3 papers)
- Partner nations
- United StatesIndia
In The Last Decade
Uttaran Bhattacharya
12 papers receiving 268 citations
Peers
Comparison fields: 5 of 35
- Computer Vision and Pattern Recognition 224
- Human-Computer Interaction 36
- Signal Processing 43
- Artificial Intelligence 85
- Control and Systems Engineering 42
Countries citing papers authored by Uttaran Bhattacharya
This map shows the geographic impact of Uttaran Bhattacharya'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 Uttaran Bhattacharya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Uttaran Bhattacharya more than expected).
Fields of papers citing papers by Uttaran Bhattacharya
This network shows the impact of papers produced by Uttaran Bhattacharya. 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 Uttaran Bhattacharya. The network helps show where Uttaran Bhattacharya may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Uttaran Bhattacharya, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 0 | |
| 7 | 2022 | 6 | |
| 8 | 2022 | 5 | |
| 9 | 2022 | 3 | |
| 10 | Text2Gestures: A Transformer-Based Network for Generating Emotive Body Gestures for Virtual Agents**This work has been supported in part by ARO Grants W911NF1910069 and W911NF1910315, and Intel. Code and additional materials available at: https: //gamma.umd.edu/t2g. | 2021 | 1 |
| 11 | 2021 | 55 | |
| 12 | 2020 | 175 | |
| 13 | Emotions Don't Lie: A Deepfake Detection Method using Audio-Visual Affective Cues | 2020 | 8 |
| 14 | 2019 | 13 | |
| 15 | 2017 | 2 |
About Uttaran Bhattacharya
Uttaran Bhattacharya is a scholar working on Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Industrial and Manufacturing Engineering, having authored 15 papers that have together received 275 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (7 papers), Human Motion and Animation (4 papers), Emotion and Mood Recognition (3 papers), Anomaly Detection Techniques and Applications (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Digital Transformation in Industry (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (224 citations), Human-Computer Interaction (36 citations) and Signal Processing (43 citations). Uttaran Bhattacharya has collaborated with scholars based in United States and India. Frequent co-authors include Dinesh Manocha, Aniket Bera, Trisha Mittal, Rohan Chandra, Kyra Kapsaskis, Tanmay Randhavane, Kurt Gray, Viswanathan Swaminathan, Venu Madhav Govindu and Stefano Petrangeli. Their work appears in journals such as arXiv (Cornell University), Proceedings of the 30th ACM International Conference on Multimedia and Proceedings of the AAAI Conference on Artificial Intelligence.
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.