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I am an Assistant Professor in the Department of Computer Science at the University of North Carolina at Charlotte. At UNC Charlotte, I am working on Video Representation Learning, and Robotic Vision. Before this, I was a Postdoctoral Associate at Stony Brook University under the supervision of Michael Ryoo. In 2020, I completed my Ph.D. in Computer Science at INRIA, Sophia Antipolis, France under the supervision of Francois Bremond and Monique Thonnat. My Ph.D. thesis is on ¨Spatio-temporal attention mechanisms for Action Recognition¨ and click here to watch my Defense Presentation. I did my Post-Grad in Computer Science from the National Institute of Technology (NIT), Rourkela. |
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I am interested in computer vision, machine learning, deep learning, and image processing. I have been mostly working on video representation learning including spatio-temporal attention mechanisms, cross-modal attention mechanisms, cross-modal knowledge distillation, and self-supervised learning for applications like action classification in trimmed videos, temporal action detection in untrimmed videos, video retrieval, anomaly detection, and deepfake detection. [Hiring] I am actively looking for motivated graduate students who can conduct research with me in UNC Charlotte. If your research interest aligns with mine, please apply to the UNC Charlotte graduate application for a PhD and mention my name in your application. Please feel free to also reach out to me if you are really interested in working on this area! |
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Xiang Li, Jinghuan Shang, Srijan Das, Michael S. Ryoo. NeurIPS 2022 arXiv The impacts of the existing self-supervised losses with Joint Learning framework for RL is limited, while there is no golden method that can dominate all tasks. |
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Jinghuan Shang, Srijan Das, Michael S. Ryoo. NeurIPS 2022 arXiv / Project Page 3DTRL is a light-weighted, plug-and play layer that recovers 3D information of visual tokens and leverages it for learning viewpoint-agnostic representations. |
 
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Rui Dai, Srijan Das, Saurav Sharma, Luca Minciullo, Lorenzo Garattoni, François Brémond, Gianpiero Francesca. T-PAMI Project Link / Code TSU is a new untrimmed daily-living dataset consisting of 51 activities performed in a spontaneous manner, captured from non-optimal viewpoints. |
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Saarthak Kapse, Srijan Das, Prateek Prasanna. Arxiv Pre-print, March 2022 arXiv / code A transformer based Pyramidal Context-Detail Network that leverages complementary information from multiple resolutions in Whole slide images. |
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Srijan Das, and Michael S. Ryoo. WACV 2023 arXiv A framework for learning self-supervised video representation that is invariant to unseen camera viewpoints. |
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Srijan Das and Michael S. Ryoo. Arxiv Pre-print, December 2021 arXiv This paper focuses on designing video augmentation for self-supervised learning, we analyze the best strategy to mix videos to create a new augmented video sample. We also propose CMMC to make use of other modalities in videos for data mixing. |
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Rui Dai, Srijan Das, Kumara Kahatapitiya, Michael S. Ryoo, Francois Bremond. CVPR 2022 arXiv / code A ConvTransformer network that explores global and local temporal relations at multiple resolutions. |
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Srijan Das, Rui Dai, Di Yang, Francois Bremond, TPAMI, 2021 arXiv / code VPN++ is an extension of our VPN model (ECCV 2020). VPN++ hallucinates pose driven features while not requiring costly 3D Poses at inference. |
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Rui Dai, Srijan Das, Francois Bremond. BMVC 2021, Oral |
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Rui Dai, Srijan Das, Francois Bremond. ICCV 2021 |
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Rui Dai, Srijan Das, Luca Minciullo, Lorenzo Garattoni, Gianpiero Francesca and Francois Bremond. WACV 2021 Code / Video / Poster |
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Srijan Das, Saurav Sharma, Rui Dai, Francois Bremond, Monique Thonnat. ECCV 2020 Code |
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Srijan Das, Monique Tonnat and Francois Bremond. WACV 2020 |
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Srijan Das, Rui Dai, Michal Koperski, Luca Minciullo, Lorenzo Garattoni, Francois Bremond and Gianpiero Francesca. ICCV 2019 Project Link / Code |
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Srijan Das, Arpit Chaudhary, Francois Bremond and Monique Thonnat. WACV 2019 |
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