VideoEval-Pro: Robust and Realistic Long Video Understanding Evaluation
Wentao Ma, Weiming Ren, Yiming Jia, Zhuofeng Li, Ping Nie, Ge Zhang, Wenhu Chen
2025-05-21
Summary
This paper talks about VideoEval-Pro, a new way to test how well AI systems understand long videos by asking them open-ended questions instead of just giving them multiple-choice tests.
What's the problem?
The problem is that most current methods for checking if AI can understand long videos only use simple multiple-choice questions, which don't really show if the AI truly gets what's happening in the video.
What's the solution?
To solve this, the researchers created a new benchmark that uses open-ended questions, which means the AI has to explain its answers in its own words. This gives a much better idea of how deeply the AI understands the video content.
Why it matters?
This matters because it helps developers build smarter AI that can actually watch and understand videos like a human, which is useful for things like video search, education, and safety monitoring.
Abstract
VideoEval-Pro, a benchmark using open-ended questions, provides a more accurate measure of long video understanding compared to existing multiple-choice question benchmarks.