

Open Sora
Overview :
Open-Sora is an open-source project dedicated to efficiently generating high-quality videos, making its models, tools, and content accessible to everyone. By embracing open-source principles, Open-Sora not only democratizes access to advanced video generation technology but also provides a streamlined and user-friendly platform that simplifies the complexities of video production. Our goal is to foster innovation, creativity, and inclusive content creation through Open-Sora. Currently in its early stages, the project is actively under development. Open-Sora supports the entire video data preprocessing, accelerated training, and inference workflow. The provided weights can generate 2 seconds of 512x512 resolution video after only 3 days of training. Open-Sora has also achieved a 46% cost reduction through improved training strategies.
Target Users :
Video creation, filmmaking, educational resource generation, marketing video production, etc.
Use Cases
Produce a short promotional video for a new product launch.
Generate video demonstration tutorial resources for online educational courses.
Create a short and captivating fictional video work.
Features
Video Generation
Video Preprocessing Tools
Video Training Acceleration
Support for Official Weight Inference
Support for Various Video Resolutions
Featured AI Tools

Sora
AI video generation
17.1M

Animate Anyone
Animate Anyone aims to generate character videos from static images driven by signals. Leveraging the power of diffusion models, we propose a novel framework tailored for character animation. To maintain consistency of complex appearance features present in the reference image, we design ReferenceNet to merge detailed features via spatial attention. To ensure controllability and continuity, we introduce an efficient pose guidance module to direct character movements and adopt an effective temporal modeling approach to ensure smooth cross-frame transitions between video frames. By extending the training data, our method can animate any character, achieving superior results in character animation compared to other image-to-video approaches. Moreover, we evaluate our method on benchmarks for fashion video and human dance synthesis, achieving state-of-the-art results.
AI video generation
11.5M