activity
20142024
most citedRT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

273 citations · 865 across the 61 of their papers we have counts for

collaborators

79 papers

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…

cs.CV2024

Adaptive Caching for Faster Video Generation with Diffusion Transformers

Kumara Kahatapitiya, Haozhe Liu, Sen He +5

Generating temporally-consistent high-fidelity videos can be computationally expensive, especially over longer temporal spans. More-recent Diffusion Transformers (DiTs) -- despite…

cs.RO2024★ 2 cited

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

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.CV2024

Learning to Localize Objects Improves Spatial Reasoning in Visual-LLMs

Kanchana Ranasinghe, Satya Narayan Shukla, Omid Poursaeed +2

Integration of Large Language Models (LLMs) into visual domain tasks, resulting in visual-LLMs (V-LLMs), has enabled exceptional performance in vision-language tasks, particularly…

cs.CV2024

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…