Project Overview: StoryOS is a demo project being developed for a media company to address inconsistency issues in AI video regeneration. The goal is to create a deterministic system where video generation produces consistent, repeatable results rather than random variations.
Current AI video generation tools suffer from inconsistency in video regeneration. When you regenerate a video or make small changes, the output often varies unpredictably, causing characters to change appearance, scenes to shift, and details to morph. This inconsistency makes it impossible to maintain continuity and control in video production workflows.
I'm working on 3D rendering and point cloud technology to solve this inconsistency problem. By creating 3D representations of characters and scenes using point clouds, we can maintain consistent geometry and appearance across video regenerations. This approach ensures that when a video is regenerated or modified, the core 3D structure remains stable, eliminating the randomness that plagues current AI video tools.
The solution involves creating 3D representations of characters and scenes using point cloud technology. By maintaining consistent 3D geometry across video regenerations, we ensure that characters and objects retain their appearance and structure, eliminating the randomness that causes inconsistency in current AI video generation systems.
My work focuses specifically on the 3D rendering pipeline and point cloud generation, which form the foundation for maintaining consistency in video regeneration. This approach allows the system to preserve character identity and scene structure even when videos are regenerated or modified.