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arXiv · 2404.18620

FlexiFilm: Long Video Generation with Flexible Conditions

Yichen Ouyang·jianhao Yuan·Hao Zhao·Gaoang Wang·Bo zhao
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Abstract

Generating long and consistent videos has emerged as a significant yet challenging problem. While most existing diffusion-based video generation models, derived from image generation models, demonstrate promising performance in generating short videos, their simple conditioning mechanism and sampling strategy-originally designed for image generation-cause severe performance degradation when adapted to long video generation. This results in prominent temporal inconsistency and overexposure. Thus, in this work, we introduce FlexiFilm, a new diffusion model tailored for long video generation. Our framework incorporates a temporal conditioner to establish a more consistent relationship between generation and multi-modal conditions, and a resampling strategy to tackle overexposure. Empirical results demonstrate FlexiFilm generates long and consistent videos, each over 30 seconds in length, outperforming competitors in qualitative and quantitative analyses. Project page: https://y-ichen.github.io/FlexiFilm-Page/

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Yichen Ouyang, jianhao Yuan, Hao Zhao, Gaoang Wang, Bo zhao. 2024-04-29. FlexiFilm: Long Video Generation with Flexible Conditions. https://arxiv.org/abs/2404.18620

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