Sagnik Majumder

I am a PhD student in Computer Science at UT Austin working with Prof. Kristen Grauman. Before this, I received my MS in Computer Science at UT. I am broadly interested in computer vision and machine learning. Currently, I am working on the application of embodied and active audio-visual learning to open problems in service 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 .

CV | E-Mail | Google Scholar | Github | Twitter

Affiliations
               
BITS Pilani
2014-2018
FIAS
Summer 2017
Goethe University
2018-2019
UT Austin
2019-present

Publications
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[NEW] Active Audio-Visual Separation of Dynamic Sound Sources
Sagnik Majumder, Ziad Al-Halah, Kristen Grauman
arXiv 2022
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[NEW] Move2Hear: Active Audio-Visual Source Separation
Sagnik Majumder, Ziad Al-Halah, Kristen Grauman
ICCV 2021
paper | project | code and data

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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

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Model Agnostic Answer Reranking System for Adversarial Question Answering
Sagnik Majumder, Chinmoy Samant, Greg Durrett
EACL SRW 2021
paper

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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

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Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition
Martin Mundt, Sagnik Majumder, Iuliia Pliushch, Visvanathan Ramesh
arXiv 2019
paper | code

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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

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Rethinking Layer-wise Feature Amounts in Convolutional Neural Network Architectures
Martin Mundt, Sagnik Majumder, Tobias Weis, Visvanathan Ramesh
NeurIPS CRACT Workshop 2018
paper | code

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Handwritten Digit Recognition by Elastic Matching
Sagnik Majumder, Christoph von der Malsburg, Aashish Richhariya, Surekha Bhanot
JCP 2018
paper | code

News
May 2022 Will join Meta Reality Labs Redmond as a research intern this summer.
Feb 2022 Co-organzing the SoundSpaces Challenge at the CVPR 2022 Embodied AI Workshop.
Jan 2022 Ported my old webpage to this new one. Will try to regulary update this space from now on!

Template credits: Unnat, Changan and Jon