activity
20222026
most citedFoundation Models for Video Understanding: A Survey

4 citations · 5 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CV2026

Position Aware Layer Queries for Test Time Training in Vision Language Models

Rajat Modi, Priyank Pathak, Xin Liang +1

Test-Time Training (TTT) adapts models to incoming test samples (e.g. out-of-distribution, (OOD)) when conventional fine-tuning is infeasible. Existing TTT methods for Vision-Langu…

cs.AI2026

Modern GLOM: Canonical locks that encode part-whole hierarchies

Rajat Modi, Yogesh Singh Rawat

One of the challenges in representational learning is how to encode part-whole hierarchies in a neural net. Prior works rely on flattening tree-like structures into string-like seq…

cs.CV2026

Forget, Anticipate and Adapt: Test Time Training for Long Videos

Rajat Modi, Sebastian Noel, Xin Liang +1

Test Time Training (TTT) is a mechanism in which a model adapts to an incoming test-sample by performing some self-supervised (SSL) task and updating its weights even during infere…

cs.CV2026

Sky2Ground: A Benchmark for Site Modeling under Varying Altitude

Zengyan Wang, Sirshapan Mitra, Rajat Modi +2

We introduce Sky2Ground, a three-view dataset designed for varying altitude camera localization, correspondence learning, and reconstruction. The dataset combines structured synthe…

cs.CV2024

Asynchronous Perception Machine For Efficient Test-Time-Training

Rajat Modi, Yogesh Singh Rawat

In this work, we propose Asynchronous Perception Machine (APM), a computationally-efficient architecture for test-time-training (TTT). APM can process patches of an image one at a…

cs.CV2024★ 1 cited

On Occlusions in Video Action Detection: Benchmark Datasets And Training Recipes

Rajat Modi, Vibhav Vineet, Yogesh Singh Rawat

This paper explores the impact of occlusions in video action detection. We facilitate this study by introducing five new benchmark datasets namely O-UCF and O-JHMDB consisting of s…

cs.CV2024★ 4 cited

Foundation Models for Video Understanding: A Survey

Neelu Madan, Andreas Moegelmose, Rajat Modi +2

Video Foundation Models (ViFMs) aim to learn a general-purpose representation for various video understanding tasks. Leveraging large-scale datasets and powerful models, ViFMs achi…

cs.CV2022

Video Action Detection: Analysing Limitations and Challenges

Rajat Modi, Aayush Jung Rana, Akash Kumar +4

Beyond possessing large enough size to feed data hungry machines (eg, transformers), what attributes measure the quality of a dataset? Assuming that the definitions of such attribu…