2 citations · 3 across the 7 of their papers we have counts for
5 papers · 1 filter
Reinforcement Learning meets Masked Video Modeling : Trajectory-Guided Adaptive Token Selection
Ayush K. Rai, Kyle Min, Tarun Krishna +3
Masked video modeling~(MVM) has emerged as a highly effective pre-training strategy for visual foundation models, whereby the model reconstructs masked spatiotemporal tokens using…
Video Anomaly Detection via Spatio-Temporal Pseudo-Anomaly Generation : A Unified Approach
Ayush K. Rai, Tarun Krishna, Feiyan Hu +4
Video Anomaly Detection (VAD) is an open-set recognition task, which is usually formulated as a one-class classification (OCC) problem, where training data is comprised of videos w…
Motion Aware Self-Supervision for Generic Event Boundary Detection
Ayush K. Rai, Tarun Krishna, Julia Dietlmeier +3
The task of Generic Event Boundary Detection (GEBD) aims to detect moments in videos that are naturally perceived by humans as generic and taxonomy-free event boundaries. Modeling…
Dynamic Channel Selection in Self-Supervised Learning
Tarun Krishna, Ayush K. Rai, Yasser A. D. Djilali +3
Whilst computer vision models built using self-supervised approaches are now commonplace, some important questions remain. Do self-supervised models learn highly redundant channel…
Discerning Generic Event Boundaries in Long-Form Wild Videos
Ayush K Rai, Tarun Krishna, Julia Dietlmeier +3
Detecting generic, taxonomy-free event boundaries invideos represents a major stride forward towards holisticvideo understanding. In this paper we present a technique forgeneric ev…