Ayush Gupta

I am a Ph.D. student at Johns Hopkins University in the department of Computer Science. I am advised by Prof. Rama Chellappa working on problems in Computer Vision and Machine Learning. I am supported by an IARPA grant, BRIAR. I am currently working on problems related to fine-grained computer vision and metric learning.

Previously I obtained a B.E. in Computer Science from Birla Institute of Technology and Science (BITS), Pilani. At BITS Pilani I was working under the guidance of Prof. Poonam Goyal on generating natural language descriptions of videos, and Dr. Yogesh S Rawat on Gait Recognition.

Email / CV / Google Scholar / Twitter / Github

News

10/2024: Our paper MimicGait: A Model-Agnostic Approach for Occluded Gait Recognition using Correlational Knowledge Distillation has been accepted to WACV 2025!
09/2024: Our paper GaitContour: Efficient Gait Recognition based on a Contour-Pose Representation has been accepted to WACV 2025!
05/2024: Starting a summer internship at SRI! I will be working on vision-language models.
04/2024: Our paper "Tackling Domain Shifts in Person Re-Identification: A Survey and Analysis" has been accepted at the CVPR 2024 Continual Learning Workshop!
10/2023: Our paper You Can Run but not Hide: Improving Gait Recognition with Intrinsic Occlusion Type Awareness is accepted as an oral paper at WACV 2024! See you in Hawaii!
08/2023: Starting a Teaching Assistantship in the Machine Perception course for Fall 2023
08/2022: Joined the AIEM Lab as a PhD student at Johns Hopkins University! I will be working on BRIAR, an IARPA grant.
05/2021: Started collaborating with CRCV Lab at UCF for undergraduate thesis
09/2020: Started working with the Language Technology Group at University of Hamburg on the CLARIN COVID Disinformation Hackathon
05/2020: Started internship at Indian Institute of Remote Sensing, ISRO

Research

I am interested in all things computer vision and machine learning. Specifically, my current research interests are in Multimodal LLMs, where I am working on making LLMs see the world like humans do. I also work on Gait Recognition and Person Re-ID, on vision models which can identify people from long-range, turbulent, in-the-wild data.

	TOGA: Temporally Grounded Open-Ended Video QA with Weak Supervision Ayush Gupta, Anirban Roy, Rama Chellappa, Nathaniel D. Bastian, Alvaro Velasquez, Susmit Jha under submission We use multimodal LLMs for temporal grounding of question-answer pairs in unconstrained videos.
	You Can Run but not Hide: Improving Gait Recognition with Intrinsic Occlusion Type Awareness Ayush Gupta, Rama Chellappa WACV 2024 (Oral) We use an auxiliary occlusion detector to solve the occlusion problem in long range gait recognition. Project Website / arXiv
	MimicGait: A Model-Agnostic Approach for Occluded Gait Recognition using Correlational Knowledge Distillation Ayush Gupta, Rama Chellappa WACV 2025 We tackle the occlusion problem in gait recognition using correlational knowledge distillation. Project Website / arXiv
	GaitContour: Efficient Gait Recognition based on a Contour-Pose Representation Yuxiang Guo, Anshul Shah, Jiang Liu, Ayush Gupta, Cheng Peng, Rama Chellappa WACV 2025 We develop a novel, efficient contour-based representation for gait recognition. arXiv
	EchoSAM: Predicting Ejection Fraction using Segmentation Guided Vision Transformers Basudha Pal, Ayush Gupta ,Vishal Patel Predicting the Ejection Fraction from ultrasound images of the heart, utilizing the Segment Anything Model.
	Tackling Domain Shifts in Person Re-Identification: A Survey and Analysis Vuong Nguyen, Samiha Mirza, Abdollah Zakeri, Ayush Gupta, Rahma Aloui, Khadija Khaldi, Pranav Mantini, Shishir Shah, Fatima Merchant CVPR 2024 Continual Learning Workshop A survey on domain shift in Person Re-ID. Paper
	GaitZero: Temporal Self-similarity for Unsupervised Gait Recognition Ayush Gupta, Alexander Matasa, Shruti Vyas, Yogesh S Rawat Developing a novel technique for unsupervised gait recognition using temporal self similarity.
	Visually Guided Knowledge selection for Video Captioning Ayush Gupta, Ashrya Agrawal, Poonam Goyal, Navneet Goyal An approach for generating natural language captions of videos using external knowledge bases. Paper

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