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VITA lab at EPFL avatar

Stable Video Infinity

Research code and weights for generating very long videos without drift

  • AI media
  • AI models and runtimes
View on GitHub
Website

What it is

A research project from EPFL's VITA lab that extends video diffusion transformers built on Wan 2.1 and 2.2 so they can produce minutes-long videos without the color drift and quality loss that usually build up across clips. It trains the model to correct its own accumulated errors, and ships LoRA-style weights, a benchmark dataset, and variants for talking faces, dance, and cartoon footage. Researchers and ComfyUI users run it to chain prompts into long single-shot or multi-shot sequences.

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Facts

Stars
2,590 GitHub stars.
2,590

Forks
231
Commits
66
Contributors
2
Language
Python
License
MIT
Last commit
Sep 17, 2026
On GitHub since
October 2025
Platforms
Linux, library
Self-hostable
No
Alternative to
Sora, Runway
Tags
  • video-generation
  • open-weights
  • machine-learning

Last synced from GitHub on Oct 20, 2026

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