6 papers
TimeProVe: Propose, then Verify for Efficient Long Video Temporal Reasoning in Activities of Daily Living
Arkaprava Sinha, Dominick Reilly, Siddharth Krishnan +2
Long Video Question Answering (LVQA) requires identifying sparse, query-relevant evidence within hours-long untrimmed videos. Existing approaches either process videos densely with…
UNIEGO: Proxies as Mediators for Unified Egocentric Video Representation Learning
Wenhao Chi, Arkaprava Sinha, Dominick Reilly +2
Egocentric video understanding is inherently limited by the narrow perspective of wearable cameras: a single viewpoint, a single modality, a single model cannot capture the full ri…
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…
DiffSwap++: 3D Latent-Controlled Diffusion for Identity-Preserving Face Swapping
Weston Bondurant, Arkaprava Sinha, Hieu Le +2
Diffusion-based approaches have recently achieved strong results in face swapping, offering improved visual quality over traditional GAN-based methods. However, even state-of-the-a…
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…
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…