MuseV
| Property | Value |
|---|---|
| License | CreativeML OpenRAIL-M |
| Developer | TMElyralab |
| Primary Use | Text-to-Video Generation |
| Paper | Coming Soon |
What is MuseV?
MuseV is a groundbreaking diffusion-based virtual human video generation framework developed by Lyra Lab at Tencent Music Entertainment. Released in March 2024, it represents a significant advancement in AI-driven video generation, particularly focusing on infinite-length video creation and high-fidelity output.
Implementation Details
The model employs a novel Visual Conditioned Parallel Denoising scheme, enabling it to generate consistent, high-quality videos of unlimited length. It's built on the Stable Diffusion ecosystem and supports multiple reference image technologies including IPAdapter, ReferenceOnly, ReferenceNet, and IPAdapterFaceID.
- Supports Image2Video, Text2Image2Video, and Video2Video generation
- Compatible with Stable Diffusion ecosystem components (base_model, lora, controlnet)
- Trained on human dataset with 512x320 resolution capability
- Implements parallel denoising for stable long-form generation
Core Capabilities
- Infinite-length video generation with consistent quality
- High-fidelity virtual human animation
- Multiple input modes (text, image, video)
- Advanced pose control and reference image processing
- Real-time high-quality lip sync (upcoming MuseTalk feature)
Frequently Asked Questions
Q: What makes this model unique?
MuseV's ability to generate infinite-length videos while maintaining consistency and quality through its Visual Conditioned Parallel Denoising scheme sets it apart from other video generation models.
Q: What are the recommended use cases?
The model excels in virtual human video generation, particularly for creating talking head videos, human animations, and scene transitions. It's particularly suited for content creation, virtual presenters, and digital human applications.
