UltraVideo: High-Quality UHD Video Dataset with Comprehensive Captions
Journal:
arXiv
Published Date:
Jun 16, 2025
Abstract
The quality of the video dataset (image quality, resolution, and fine-grained
caption) greatly influences the performance of the video generation model. The
growing demand for video applications sets higher requirements for high-quality
video generation models. For example, the generation of movie-level Ultra-High
Definition (UHD) videos and the creation of 4K short video content. However,
the existing public datasets cannot support related research and applications.
In this paper, we first propose a high-quality open-sourced UHD-4K (22.4\% of
which are 8K) text-to-video dataset named UltraVideo, which contains a wide
range of topics (more than 100 kinds), and each video has 9 structured captions
with one summarized caption (average of 824 words). Specifically, we carefully
design a highly automated curation process with four stages to obtain the final
high-quality dataset: \textit{i)} collection of diverse and high-quality video
clips. \textit{ii)} statistical data filtering. \textit{iii)} model-based data
purification. \textit{iv)} generation of comprehensive, structured captions. In
addition, we expand Wan to UltraWan-1K/-4K, which can natively generate
high-quality 1K/4K videos with more consistent text controllability,
demonstrating the effectiveness of our data curation.We believe that this work
can make a significant contribution to future research on UHD video generation.
UltraVideo dataset and UltraWan models are available at
https://xzc-zju.github.io/projects/UltraVideo.
