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cs.CV2025
MS-Temba: Multi-Scale Temporal Mamba for Understanding Long Untrimmed Videos
Arkaprava Sinha, Monish Soundar Raj, Pu Wang +3
Temporal Action Detection (TAD) in untrimmed videos poses significant challenges, particularly for Activities of Daily Living (ADL) requiring models to (1) process long-duration vi…
cs.CV2025
LLAVIDAL: A Large LAnguage VIsion Model for Daily Activities of Living
Dominick Reilly, Rajatsubhra Chakraborty, Arkaprava Sinha +5
Current Large Language Vision Models (LLVMs) trained on web videos perform well in general video understanding but struggle with fine-grained details, complex human-object interact…
cs.CV2025
SKI Models: Skeleton Induced Vision-Language Embeddings for Understanding Activities of Daily Living
Arkaprava Sinha, Dominick Reilly, Francois Bremond +2
The introduction of vision-language models like CLIP has enabled the development of foundational video models capable of generalizing to unseen videos and human actions. However, t…