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stepfun-ai avatar

stepfun-ai/Step-Video-T2V

0
View on GitHub↗
3,186 stars·338 forks·Python·MIT·13 views

Step Video T2V

   

Features

  • Foundation Models - Technical implementation of video foundation models.
  • Video Generation - Text-to-video generation model.
  • Video Generation Models - Text-to-video generation model for creative applications.

Star history

Star history chart for stepfun-ai/step-video-t2vStar history chart for stepfun-ai/step-video-t2v

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Frequently asked questions

What does stepfun-ai/step-video-t2v do?

   

What are the main features of stepfun-ai/step-video-t2v?

The main features of stepfun-ai/step-video-t2v are: Foundation Models, Video Generation, Video Generation Models.

Which projects share features with stepfun-ai/step-video-t2v?

Projects with overlapping indexed features include: skyworkai/skyreels-v2 — SkyReels-V2 is a video generation system that creates, extends, and refines video clips from text descriptions,… tencent/hunyuanvideo. lightricks/ltx-video. pku-yuangroup/open-sora-plan — Open-Sora-Plan is a text-to-video framework and distributed video training system. It utilizes a diffusion transformer… hpcaitech/open-sora — Open-Sora is a video generation framework designed to produce cinematic sequences from text prompts and images. It… wan-video/wan2.1 — Wan2.1 is a generative video synthesis framework that provides foundation models for creating high-fidelity video…

Projects sharing features with Step Video T2V

These projects share indexed features with Step Video T2V. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • lightricks/ltx-videoLightricks avatar

    Lightricks/LTX-Video

    9,324View on GitHub↗
    Pythondiffusion-modelsditimage-to-video
    View on GitHub↗9,324
  • pku-yuangroup/open-sora-planPKU-YuanGroup avatar

    PKU-YuanGroup/Open-Sora-Plan

    12,163View on GitHub↗

    Open-Sora-Plan is a text-to-video framework and distributed video training system. It utilizes a diffusion transformer architecture and large language model components to transform written descriptions or image prompts into high-quality video sequences. The system features a distributed infrastructure designed for large-scale video training and inference. It employs sequence parallelism to split high-resolution or long-duration video samples across multiple GPUs and uses a sparse attention mechanism to increase processing speed. The project includes capabilities for both text-to-video and im

    Python
    View on GitHub↗12,163
  • hpcaitech/open-sorahpcaitech avatar

    hpcaitech/Open-Sora

    29,101View on GitHub↗

    Open-Sora is a video generation framework designed to produce cinematic sequences from text prompts and images. It functions as a generative system that transforms written descriptions or reference images into video content featuring realistic textures and lighting. The project includes a dedicated prompt engineering tool that uses large language models to expand simple user inputs into detailed descriptions. It also features a motion controller for adjusting movement intensity in generated sequences and evaluating motion levels in existing video files. The framework incorporates text-to-vid

    Python
    View on GitHub↗29,101
  • skyworkai/skyreels-v2SkyworkAI avatar

    SkyworkAI/SkyReels-V2

    6,356View on GitHub↗

    SkyReels-V2 is a video generation system that creates, extends, and refines video clips from text descriptions, images, or both. It operates as a diffusion-based video generation model that can produce videos of any duration by denoising frames sequentially, with each new frame conditioned on the ones that came before it. The system supports generating videos from scratch using text prompts, starting from a single image and producing subsequent frames, or constraining both the first and last frames to match user-provided images. What distinguishes SkyReels-V2 is its combination of infinite-le

    Python
    View on GitHub↗6,356
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