Sagnik Majumder

I am a PhD student in Computer Science at UT Austin, advised by Prof. Kristen Grauman. Before this, I received my MS in Computer Science at UT. I am broadly interested in computer vision and machine learning. My current line of research is multi-modal understanding of 3D scenes and human activity, with applications in mobile robotics and AR/VR.

Previously, I have worked with Prof. Visvanathan Ramesh at Goethe University on continual and meta learning for image recognition tasks. I have also had the pleasure of collaborating with Prof. Christoph Malsburg at the Frankfurt Institute for Advanced Studies for investigating visual models that draw motivation from Neuroscience.

Earlier, I graduated from BITS Pilani.

Full-time industrial research roles: I am looking for full-time industrial research roles in multi-modal video understanding and/or synthesis starting in Summer/Fall 2026. Kindly reach out if you think I would be a good fit.

Research collaborations: I am open to collaborating on research projects, and also mentoring Master's and final (senior) year students on their thesis. Shoot me an email to discuss more.

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Affiliations


BITS Pilani 2014-2018	Goethe University / FIAS 2017-2019	Meta AI 2022-2024	Apple AI 2025-	UT Austin 2019-present

News

June 2025	Joined Apple Computer Vision as a research intern this summer.
May 2025	Recognized as an Outstanding Reviewer for CVPR 2025.
Apr 2025	Passed my PhD proposal. Officially a candidate now!
Apr 2025	LangView is selected as Highlight at CVPR 25.
July 2024	ActiveRIR is selected as Oral at IROS 24.
June 2024	Invited talks at Sight and Sound and EgoVis workshops at CVPR on "Learning Spatial Features from Audio-Visual Correspondence in Egocentric Videos".
May 2024	ActiveRIR is covered by TechXplore.
May 2024	Ego-Exo4D is selected as Oral (0.8% selection rate) at CVPR 24.
Mar 2024	Two papers, Learning Spatial Features from Audio-Visual Correspondence in Egocentric Videos and Ego-Exo4D got accepted at CVPR 24.
June 2023	Invited talk at CVPR 23 Sight and Sound Workshop on "Chat2Map: Efficient Scene Mapping from Multi-Ego Conversations".
May 2023	Invited talk at JHU NSA Lab on "Efficiently understanding 3D scenes using sight and sound".
Mar 2023	Our paper Chat2Map: Efficient Scene Mapping from Multi-Ego Conversations. got accepted at CVPR 23.
Feb 2023	Co-organzing the CVPR 2023 SoundSpaces Challenge and the Embodied AI Workshop.
Dec 2022	Starting as a visiting researcher at Meta AI Research.
Oct 2022	Invited talk at ECCV 22 AV4D Workshop on "Active Audio-Visual Separation of Dynamic Sound Sources".
Sept 2022	Our paper Few-Shot Audio-Visual Learning of Environment Acoustics got accepted at NeurIPS 22.
Sept 2022	Continuing as a student researcher at Meta Reality Labs Redmond this Fall.
July 2022	Our paper Active Audio-Visual Separation of Dynamic Sound Sources got accepted at ECCV 22.
June 2022	Invited talk at CVPR 22 Sight and Sound Workshop on "Active Audio-Visual Separation of Dynamic Sound Sources" (Slides).
June 2022	Joined Meta Reality Labs Redmond as a research scientist intern this summer.
April 2022	Invited talk at Meta AI Research on "Active Audio-Visual Separation of Dynamic Sound Sources" (Slides).
Feb 2022	Co-organzing the SoundSpaces Challenge at the CVPR 2022 Embodied AI Workshop.

Publications

	Switch-a-View: View Selection Learned from Unlabeled In-the-wild Videos Sagnik Majumder, Tushar Nagarajan, Ziad Al-Halah, Kristen Grauman ICCV 2025 paper \| project
	Which Viewpoint Shows it Best? Language for Weakly Supervising View Selection in Multi-view Videos Sagnik Majumder, Tushar Nagarajan, Ziad Al-Halah, Reina Pradhan, Kristen Grauman CVPR 2025 (Highlight) paper \| project
	ActiveRIR: Active Audio-Visual Exploration for Acoustic Environment Modeling Arjun Somayazulu, Sagnik Majumder, Changan Chen, Kristen Grauman IROS 2024 (Oral) paper \| project \| Media coverage: TechXplore
	Learning Spatial Features from Audio-Visual Correspondence in Egocentric Videos Sagnik Majumder, Ziad Al-Halah, Kristen Grauman CVPR 2024 paper \| project \| code and data
	Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives Kristen Grauman, Andrew Westbury, Lorenzo Torresani, ..., Sagnik Majumder, ..., Mike Zheng Shou, Michael Wray CVPR 2024 (Oral) paper \| project
	Chat2Map: Efficient Scene Mapping from Multi-Ego Conversations Sagnik Majumder, Hao Jiang, Pierre Moulon, Ethan Henderson, Paul Calamia, Kristen Grauman, Vamsi Krishna Ithapu Equal contribution CVPR 2023* paper \| project \| code and data
	Retrospectives on the Embodied AI Workshop Matt Deitke, Dhruv Batra, Yonatan Bisk, ..., Sagnik Majumder, ..., Luca Weihs, Jiajun Wu arXiv paper
	Few-Shot Audio-Visual Learning of Environment Acoustics Sagnik Majumder, Changan Chen, Ziad Al-Halah, Kristen Grauman Equal contribution NeurIPS 2022* paper \| project \| code and data
	Active Audio-Visual Separation of Dynamic Sound Sources Sagnik Majumder, Kristen Grauman ECCV 2022 paper \| project \| code and data
	Move2Hear: Active Audio-Visual Source Separation Sagnik Majumder, Ziad Al-Halah, Kristen Grauman ICCV 2021 paper \| project \| code and data
	Learning to Set Waypoints for Audio-Visual Navigation Changan Chen, Sagnik Majumder, Ziad Al-Halah, Ruohan Gao, Santhosh K. Ramakrishnan, Kristen Grauman ICLR 2021 paper \| project \| code
	Model Agnostic Answer Reranking System for Adversarial Question Answering Sagnik Majumder, Chinmoy Samant, Greg Durrett EACL SRW 2021 paper
	Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset Martin Mundt, Sagnik Majumder, Sreenivas Murali, Panagiotis Panetsos, Visvanathan Ramesh CVPR 2021 paper \| code and data
	Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition Martin Mundt, Sagnik Majumder, Iuliia Pliushch, Visvanathan Ramesh arXiv 2019 paper \| code
	Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers? Martin Mundt, Iuliia Pliushch, Sagnik Majumder, Visvanathan Ramesh ICCV SDLCV Workshop 2019 paper \| code
	Rethinking Layer-wise Feature Amounts in Convolutional Neural Network Architectures Martin Mundt, Sagnik Majumder, Tobias Weis, Visvanathan Ramesh NeurIPS CRACT Workshop 2018 paper \| code
	Handwritten Digit Recognition by Elastic Matching Sagnik Majumder, Christoph von der Malsburg, Aashish Richhariya, Surekha Bhanot JCP 2018 paper \| code

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