The I2VGen-XL model, leveraging advances in diffusion models, addresses key challenges in video synthesis like semantic accuracy and spatio-temporal continuity, using a two-stage process focused on semantics and refinement. It utilizes a vast dataset of 35 million text-video and 6 billion text-image pairs to enhance detail continuity and clarity in videos. Extensive testing confirms I2VGen-XL's superiority over existing methods, with plans to release its source code and models publicly.
