FlashVideo:Flowing Fidelity to Detail for Efficient High-Resolution
  Video Generation
Authors: name: Shilong Zhang, name: Wenbo Li, name: Shoufa Chen, name: Chongjian Ge, name: Peize Sun, name: Yida Zhang, name: Yi Jiang, name: Zehuan Yuan, name: Binyue Peng, name: Ping Luo

DiT diffusion models have achieved great success in text-to-video generation,
leveraging their scalability in model capacity and data scale. High content and
motion fidelity aligned with text prompts, however, often require large model
parameters and a substantial number of function evaluations (NFEs). Realistic
and visually appealing details are typically reflected in high resolution
outputs, further amplifying computational demands especially for single stage
DiT models. To address these challenges, we propose a novel two stage
framework, FlashVideo, which strategically allocates model capacity and NFEs
across stages to balance generation fidelity and quality. In the first stage,
prompt fidelity is prioritized through a low resolution generation process
utilizing large parameters and sufficient NFEs to enhance computational
efficiency. The second stage establishes flow matching between low and high
resolutions, effectively generating fine details with minimal NFEs.
Quantitative and visual results demonstrate that FlashVideo achieves
state-of-the-art high resolution video generation with superior computational
efficiency. Additionally, the two-stage design enables users to preview the
initial output before committing to full resolution generation, thereby
significantly reducing computational costs and wait times as well as enhancing
commercial viability .