VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models

Understand

Text-to-video generation aims to produce a video based on a given prompt.

• Recently, several commercial video models have been able to generate plausible videos with minimal noise, excellent details, and high aesthetic scores.
• However, these models rely on large-scale, well-filtered, high-quality videos that are not accessible to the community.
• Many existing research works, which train models using the low-quality WebVid-10M dataset, struggle to generate high-quality videos because the models are optimized to fit WebVid-10M.