What Is That Talk About? A Video-to-Text Summarization Dataset for Scientific Presentations
Year: 2025
Type: conference-paper
Abstract: Transforming recorded videos into concise and accurate textual summaries is a growing challenge in multimodal learning.This paper introduces VISTA, a dataset specifically designed for video-to-text summarization in scientific domains.VISTA contains 18,599 recorded AI conference presentations paired with their corresponding paper abstracts.We benchmark the performance of state-of-the-art large models and apply a plan-based framework to better capture the structured nature of abstracts.Both human and automated evaluations confirm that explicit planning enhances summary quality and factual consistency.However, a considerable gap remains between models and human performance, highlighting the challenges of our dataset.This study aims to pave the way for future research on scientific video-totext summarization.The project information is available at https://dongqi.me/projects/VISTA.
Authors: Dongqi Liu, Chenxi Whitehouse, Xi Yu, Louis Mahon, Rohit Saxena, Zheng Zhao, Yifu Qiu, Mirella Lapata, Vera Demberg
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
Award: G5730701950
OpenAlex ID: W4412945704