Prithvijit Chattopadhyay

prithvijit3 [at] gatech [dot] edu

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I am a final year CS Ph.D. student at Georgia Tech, advised by Prof. Judy Hoffman. I am broadly interested in problems at the intersection of Computer Vision and Machine Learning. Despite their remarkable success, computer vision systems often exhibit aberrant behaviors (reduced performance, uncalibrated predictions, etc.) under distribution shifts. My doctoral research (so far) has focused on the problem of out-of-distribution generalization – how can we develop computer vision systems that can generalize or adapt across changing conditions in a reliable manner?

My research has made progress along the following fundamental steps to be closer to accomplishing this goal:

Before this, I earned my Masters in Computer Science (awarded M.S. Research Award) in Spring 2019 from Georgia Tech, advised by Prof. Devi Parikh and Prof. Dhruv Batra, where I worked on a host of vision-language & ML problems – exploring human-AI teams to evaluate explanations, improving responses of & developing cooperative testing for conversational agents, zero-shot transfer, state abstraction in RL and scene-understanding. I earned my Bachelors in Electrical Engineering in 2016 from Delhi Technological University, India, where I worked on developing (now outdated) autonomous underwater vehicles (AUVs).

In past years, I have had the fortune to conduct research at PRIOR, Allen Institute of Artificial Intelligence (Summer 2022, Summer 2020) mentored by Ani Kembhavi & Roozbeh Mottaghi; Deep Learning Group, Microsoft Research Redmond (Summer 2018) mentored by Hamid Palangi; Robotics Research Lab, IIIT Hyderabad (Winter 2014) mentored by Dr. K. Madhava Krishna and Indian Association for the Cultivation of Science (IACS), Kolkata (Summer 2014) mentored by Dr. Soumitra Sengupta on a diverse set of topics - ranging from embodied AI, vision & language to physics.

I also actively participate in reviewing for top computer vision and machine learning conferences & workshops (have accumulated a few reviewer awards - CVPR 2023, CVPR 2022, CVPR 2021, ICLR 2022, MLRC 2021, ICML 2020, NeurIPS 2019, ICLR 2019, NeurIPS 2018 - in the process).


Winter 2014



Summer 2018

Summer 2020, 2022




SkyScenes: A Synthetic Dataset for Aerial Scene Understanding Sahil Khose*, Anisha Pal*, Aayushi Agarwal*, Deepanshi*, Judy Hoffman, Prithvijit Chattopadhyay ECCV 2024 [PDF] [Data] [TL;DR] Thumbnail

AUGCAL: Improving Sim2Real Adaptation by Uncertainty Calibration on Augmented Synthetic Images Prithvijit Chattopadhyay, Bharat Goyal, Boglarka Ecsedi, Viraj Prabhu, Judy Hoffman ICLR 2024 Workshop on Uncertainty Quantification for Computer Vision, ICCV 2023 (Extended Abstract) [PDF] [TL;DR] Thumbnail

We're Not Using Videos Effectively: An Updated Domain Adaptive Video Segmentation Baseline Simar Kareer, Vivek Vijaykumar, Harsh Maheshwari, Prithvijit Chattopadhyay, Judy Hoffman, Viraj Prabhu TMLR 2024 [PDF] [Code] [TL;DR] Thumbnail

Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks Micah Goldblum*, Hossein Souri*, Renkun Ni, Manli Shu, Viraj Uday Prabhu, Gowthami Somepalli, Prithvijit Chattopadhyay, Adrien Bardes, Mark Ibrahim, Judy Hoffman, Rama Chellappa, Andrew Gordon Wilson, Tom Goldstein NeurIPS Datasets and Benchmarks 2023 [PDF] [Code] [TL;DR] Thumbnail

LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images Viraj Prabhu, Sriram Yenamandra, Prithvijit Chattopadhyay, Judy Hoffman NeurIPS 2023 [PDF] [code] [project page] [TL;DR] Thumbnail

Benchmarking Low-Shot Robustness to Natural Distribution Shifts Aaditya Singh, Kartik Sarangmath, Prithvijit Chattopadhyay, Judy Hoffman ICCV 2023 [PDF] [code] [TL;DR] Thumbnail

PASTA: Proportional Amplitude Spectrum Training Augmentation for Syn-to-Real Domain Generalization Prithvijit Chattopadhyay*, Kartik Sarangmath*, Vivek Vijaykumar, Judy Hoffman ICCV 2023 [PDF] [code] [TL;DR] Thumbnail

RobustNav: Towards Benchmarking Robustness in Embodied Navigation Prithvijit Chattopadhyay, Judy Hoffman, Roozbeh Mottaghi, Ani Kembhavi ICCV 2021 Oral presentation [PDF] [code] [project page] [video] [TL;DR] Thumbnail

Likelihood Landscapes: A Unifying Principle Behind Many Adversarial Defenses Fu Lin, Rohit Mittapali, Prithvijit Chattopadhyay, Daniel Bolya, Judy Hoffman Adversarial Robustness in the Real World (AROW), ECCV 2020 NVIDIA Best Paper Runner Up [PDF] [video] [TL;DR] Thumbnail

Learning to Balance Specificity and Invariance for In and Out of Domain Generalization Prithvijit Chattopadhyay, Yogesh Balaji, Judy Hoffman ECCV 2020 Visual Learning with Limited Labels (LwLL), CVPR 2020 [PDF] [code] [video] [TL;DR] Thumbnail

Improving Generative Visual Dialog by Answering Diverse Questions Vishvak Murahari, Prithvijit Chattopadhyay, Dhruv Batra, Devi Parikh, Abhishek Das EMNLP 2019 Visual Question Answering and Dialog Workshop, CVPR 2019 [PDF] [code] [TL;DR] Thumbnail

IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma, Abhishek Das,
Devi Parikh, Dhruv Batra, Ramakrishna Vedantam
IJCAI 2020 Workshop on Task Agnostic Reinforcement Learning (TARL), ICLR 2019 [PDF] [TL;DR] Thumbnail

EvalAI: Towards Better Evaluation Systems for AI Agents Deshraj Yadav, Rishabh Jain, Harsh Agrawal, Prithvijit Chattopadhyay, Taranjeet Singh,
Akash Jain, Shiv Baran Singh, Stefan Lee, Dhruv Batra
Workshop on AI Systems, SOSP 2019 [PDF] [code] [TL;DR] Thumbnail

Choose Your Neuron: Incorporating Domain-Knowledge through Neuron-Importance Ramprasaath R. Selvaraju*, Prithvijit Chattopadhyay*, Mohamed Elhoseiny,
Tilak Sharma, Dhruv Batra, Devi Parikh, Stefan Lee
ECCV, 2018 Continual Learning Workshop, NeurIPS 2018 Visually Grounded Interaction and Language (ViGIL) Workshop, NeurIPS 2018 [PDF] [code] [article] [TL;DR] Thumbnail

Do explanation modalities make VQA Models more predictable to a human? Arjun Chandrasekaran*, Viraj Prabhu*, Deshraj Yadav*, Prithvijit Chattopadhyay*, Devi Parikh EMNLP 2018 [PDF] [TL;DR] Thumbnail

Evaluating Visual Conversational Agents via Cooperative Human-AI Games Prithvijit Chattopadhyay*, Deshraj Yadav*, Viraj Prabhu, Arjun Chandrasekaran, Abhishek Das, Stefan Lee, Dhruv Batra, Devi Parikh HCOMP 2017 Oral presentation [PDF] [code] [TL;DR] Thumbnail

It Takes Two to Tango: Towards Theory of AI's Mind Arjun Chandrasekaranu*, Deshraj Yadav*, Prithvijit Chattopadhyay*, Viraj Prabhu*, Devi Parikh Chalearn Looking at People Workshop, CVPR 2017 [PDF] [code] [TL;DR] Thumbnail

Counting Everyday Objects in Everyday Scenes Prithvijit Chattopadhyay*, Ramakrishna Vedantam*, Ramprasaath R. Selvaraju, Dhruv Batra, Devi Parikh CVPR 2017 Spotlight presentation [PDF] [code] [TL;DR] Thumbnail


Investigating Visual Dialog Models for Goal-Driven Self-Talk Prithvijit Chattopadhyay (advised by Devi Parikh) 2019 [Report PDF]

Exploring Weak-Supervision and Generative Models for Semantic Segmentation 2018 Prithvijit Chattopadhyay, Ramprasaath R. Selvaraju, Viraj Prabhu [Report PDF]

DTU AUV: Autonomous Underwater Vehicle Prithvijit Chattopadhyay (Acoustics & Control Systems Department) (co-authored with DTU AUV members) 2012-2016 [Report PDF]


Evaluating Visual Conversational Agents in the Context of Human-AI Cooperative Games Masters in Computer Science (specialization Machine Learning) 2017-2019 [PDF]

Professional Services

Reviewing: CVPR 2018-23, ICCV 2023, ICRA 2021-22, ECCV 2018, NeurIPS 2018-21,23, ICLR 2019-22, ICML 2019-20, ACL 2019, TPAMI

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