3 papers
cs.CV2026
VideoWeave: A Data-Centric Approach for Efficient Video Understanding
Zane Durante, Silky Singh, Arpandeep Khatua +6
Training video-language models is often prohibitively expensive due to the high cost of processing long frame sequences and the limited availability of annotated long videos. We pr…
cs.CV2025
T*: Re-thinking Temporal Search for Long-Form Video Understanding
Jinhui Ye, Zihan Wang, Haosen Sun +9
Efficiently understanding long-form videos remains a significant challenge in computer vision. In this work, we revisit temporal search paradigms for long-form video understanding…
cs.CV2025
Towards Fine-Grained Video Question Answering
Wei Dai, Alan Luo, Zane Durante +5
In the rapidly evolving domain of video understanding, Video Question Answering (VideoQA) remains a focal point. However, existing datasets exhibit gaps in temporal and spatial gra…