Dominick Reilly — accepted AI-conference papers

2025

LLAVIDAL: A Large LAnguage VIsion Model for Daily Activities of Living

Dominick Reilly, Rajatsubhra Chakraborty, Arkaprava Sinha, Manish Kumar Govind, Pu Wang, Francois Bremond +2

CVPR 2025poster

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 interactions (HOI), and view-invariant representation learning essential for Activities of Daily Living (ADL). This limitation s…

Cited by 7 Source ↗PDF ↗code ↗Scholar ↗

2025

SKI Models: Skeleton Induced Vision-Language Embeddings for Understanding Activities of Daily Living

Arkaprava Sinha, Dominick Reilly, Francois Bremond, Pu Wang, Srijan Das

AAAI 2025technical

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, these models are typically trained on web videos, which often fail to capture the challenges present in Activities of Dai…

Cited by 1 Source ↗PDF ↗code ↗Scholar ↗

2024

Just Add ?! Pose Induced Video Transformers for Understanding Activities of Daily Living

Dominick Reilly, Srijan Das

CVPR 2024poster

Video transformers have become the de facto standard for human action recognition yet their exclusive reliance on the RGB modality still limits their adoption in certain domains. One such domain is Activities of Daily Living (ADL) where RGB alone is not sufficient to distinguish between visually sim…

Cited by 19 Source ↗PDF ↗code ↗Scholar ↗