activity
20242026
collaborators

5 papers

cs.CV2026

Too Many Frames, Not All Useful: Efficient Strategies for Long-Form Video QA

Jongwoo Park, Kanchana Ranasinghe, Kumara Kahatapitiya +3

Long-form videos that span across wide temporal intervals are highly information redundant and contain multiple distinct events or entities that are often loosely related. Therefor…

cs.CV2025

Understanding Long Videos with Multimodal Language Models

Kanchana Ranasinghe, Xiang Li, Kumara Kahatapitiya +1

Large Language Models (LLMs) have allowed recent LLM-based approaches to achieve excellent performance on long-video understanding benchmarks. We investigate how extensive world kn…

cs.RO2025

LLaRA: Supercharging Robot Learning Data for Vision-Language Policy

Xiang Li, Cristina Mata, Jongwoo Park +8

Vision Language Models (VLMs) have recently been leveraged to generate robotic actions, forming Vision-Language-Action (VLA) models. However, directly adapting a pretrained VLM for…

cs.CV2024

Language Repository for Long Video Understanding

Kumara Kahatapitiya, Kanchana Ranasinghe, Jongwoo Park +1

Language has become a prominent modality in computer vision with the rise of LLMs. Despite supporting long context-lengths, their effectiveness in handling long-term information gr…

cs.CV2024

Whats in a Video: Factorized Autoregressive Decoding for Online Dense Video Captioning

AJ Piergiovanni, Dahun Kim, Michael S. Ryoo +2

Generating automatic dense captions for videos that accurately describe their contents remains a challenging area of research. Most current models require processing the entire vid…