Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k
원문 초록
Video generation models have achieved remarkable progress in the past year. The quality of AI video continues to improve, but at the cost of larger model size, increased data quantity, and greater demand for training compute. In this report, we present Open-Sora 2.0, a commercial-level video generation model trained for only $200k. With this model, we demonstrate that the cost of training a top-performing video generation model is highly controllable. We detail all techniques that contribute to this efficiency breakthrough, including data curation, model architecture, training strategy, and system optimization. According to human evaluation results and VBench scores, Open-Sora 2.0 is comparable to global leading video generation models including the open-source HunyuanVideo and the closed-source Runway Gen-3 Alpha. By making Open-Sora 2.0 fully open-source, we aim to democratize access to advanced video generation technology, fostering broader innovation and creativity in content creation. All resources are publicly available at: https://github.com/hpcaitech/Open-Sora.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting
Scaling RL to Long Videos
Omni-Video: Democratizing Unified Video Understanding and Generation
PresentAgent: Multimodal Agent for Presentation Video Generation
Lost in Latent Space: An Empirical Study of Latent Diffusion Models for Physics Emulation
Epona: Autoregressive Diffusion World Model for Autonomous Driving
토론
이 논문과 연결된 포럼 글이 아직 없습니다.