Open-Sora Plan: Open-Source Large Video Generation Model

Bin Lin, Yunyang Ge, Xinhua Cheng, Zongjian Li, Bin Zhu +19 more
11/28/2024
cs.CVcs.AI

Official code: PKU-YuanGroup/Open-Sora-Plan (12,157 stars, MIT, last commit 2026-03-08).

Abstract

We introduce Open-Sora Plan, an open-source project that aims to contribute a large generation model for generating desired high-resolution videos with long durations based on various user inputs. Our project comprises multiple components for the entire video generation process, including a Wavelet-Flow Variational Autoencoder, a Joint Image-Video Skiparse Denoiser, and various condition controllers. Moreover, many assistant strategies for efficient training and inference are designed, and a multi-dimensional data curation pipeline is proposed for obtaining desired high-quality data. Benefiting from efficient thoughts, our Open-Sora Plan achieves impressive video generation results in both qualitative and quantitative evaluations. We hope our careful design and practical experience can inspire the video generation research community. All our codes and model weights are publicly available at \url{https://github.com/PKU-YuanGroup/Open-Sora-Plan}.

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Code Implementations(1)

MIT

This project aim to reproduce Sora (Open AI T2V model), we wish the open source community contribute to this project.

12,1571,061C++, CSSFeb 20, 20247 months agoMIT

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Cite this paper

@article{lin2024opensora,
  title  = {Open-Sora Plan: Open-Source Large Video Generation Model},
  author = {Bin Lin and Yunyang Ge and Xinhua Cheng and Zongjian Li and Bin Zhu and Shaodong Wang and Xianyi He and Yang Ye and Shenghai Yuan and Liuhan Chen and Tanghui Jia and Junwu Zhang and Zhenyu Tang and Yatian Pang and Bin She and Cen Yan and Zhiheng Hu and Xiaoyi Dong and Lin Chen and Zhang Pan and Xing Zhou and Shaoling Dong and Yonghong Tian and Li Yuan},
  year   = {2024},
  eprint = {2412.00131},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2412.00131v1}
}

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