4 papers · 1 filter
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…
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…
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…
Contextual Self-paced Learning for Weakly Supervised Spatio-Temporal Video Grounding
Akash Kumar, Zsolt Kira, Yogesh Singh Rawat
In this work, we focus on Weakly Supervised Spatio-Temporal Video Grounding (WSTVG). It is a multimodal task aimed at localizing specific subjects spatio-temporally based on textua…