VideoDeepResearch: Long Video Understanding With Agentic Tool Using
Huaying Yuan, Zheng Liu, Junjie Zhou, Ji-Rong Wen, Zhicheng Dou
2025-06-15
Summary
This paper talks about VideoDeepResearch, a new AI system that understands long videos by using a text-based reasoning model combined with special tools. It can analyze and make sense of long videos better than earlier methods without needing to look at more visual details or bigger chunks of the video at once.
What's the problem?
The problem is that understanding long videos is very hard for AI because videos have a lot of information over time, and existing models struggle to keep track of everything or need to process huge amounts of visual data, which is complicated and slow.
What's the solution?
The solution was to create VideoDeepResearch, which uses a smart text-only reasoning model paired with separate tools designed to help it analyze different parts of the video step-by-step. This way, it can understand long videos effectively without requiring bigger visual input or more computing power for processing the visuals.
Why it matters?
This matters because being able to understand long videos easily helps improve many applications like video summarization, video-based learning, and content analysis. It allows AI to work faster and smarter with videos, making useful video understanding accessible for more technologies.
Abstract
VideoDeepResearch, a text-only reasoning model with modular tools, surpasses existing baselines in long video understanding tasks without extending context windows or enhancing visual perception capabilities.