activity
20242026
collaborators

8 papers

cs.CV2026

CoSPlan: Corrective Sequential Planning via Scene Graph Incremental Updates

Shresth Grover, Priyank Pathak, Akash Kumar +1

Vision Language Models (VLMs) have shown promising planning capabilities, yet their success remains confined to the text domain, leaving visual decision-making relatively underexpl…

cs.CV2026

VISTA: Video Interaction Spatio-Temporal Analysis Benchmark

Alejandro Aparcedo, Akash Kumar, Aaryan Garg +5

Existing benchmarks for Vision-Language Models (VLMs) primarily evaluate spatio-temporal understanding on simple single-action videos, closed attribute sets and restricted entity t…

cs.CV2026

RobustGait: Robustness Analysis for Appearance Based Gait Recognition

Reeshoon Sayera, Akash Kumar, Sirshapan Mitra +2

Appearance-based gait recognition have achieved strong performance on controlled datasets, yet systematic evaluation of its robustness to real-world corruptions and silhouette vari…

cs.CV2025

OmViD: Omni-supervised active learning for video action detection

Aayush Rana, Akash Kumar, Vibhav Vineet +1

Video action detection requires dense spatio-temporal annotations, which are both challenging and expensive to obtain. However, real-world videos often vary in difficulty and may n…

cs.CV2025

A Large-Scale Analysis on Contextual Self-Supervised Video Representation Learning

Akash Kumar, Ashlesha Kumar, Vibhav Vineet +1

Self-supervised learning has emerged as a powerful paradigm for label-free model pretraining, particularly in the video domain, where manual annotation is costly and time-intensive…

cs.CV2025

STPro: Spatial and Temporal Progressive Learning for Weakly Supervised Spatio-Temporal Grounding

Aaryan Garg, Akash Kumar, Yogesh S Rawat

In this work we study Weakly Supervised Spatio-Temporal Video Grounding (WSTVG), a challenging task of localizing subjects spatio-temporally in videos using only textual queries an…