stable-video-diffusion-img2vid-xt

Maintained By
stabilityai

Stable Video Diffusion Image-to-Video XT

PropertyValue
DeveloperStability AI
LicenseStable Video Diffusion Community License
Research PaperAvailable Here
GitHub Repositorygenerative-models

What is stable-video-diffusion-img2vid-xt?

Stable Video Diffusion XT is an advanced latent diffusion model designed to transform still images into dynamic video sequences. As an evolution of the original SVD model, this extended version generates 25 frames at an impressive 576x1024 resolution, offering longer and higher-quality video outputs than its predecessor.

Implementation Details

The model operates through a sophisticated latent diffusion process, utilizing a finetuned f8-decoder for enhanced temporal consistency. It builds upon the foundation of the 14-frame SVD model, extending capabilities to create longer, more stable video sequences. The implementation requires approximately 180 seconds for generation on an A100 80GB GPU.

  • Generates 25 frames from a single input image
  • Supports 576x1024 resolution output
  • Includes built-in watermarking functionality
  • Utilizes advanced temporal consistency mechanisms

Core Capabilities

  • High-quality video generation from still images
  • Superior performance compared to competitors (verified through user studies)
  • Support for both commercial and non-commercial applications
  • Built-in safety features and content filtering

Frequently Asked Questions

Q: What makes this model unique?

This model stands out for its ability to generate longer video sequences (25 frames) with improved temporal consistency and higher resolution compared to previous versions. Human evaluation studies have shown it outperforms competing solutions like GEN-2 and PikaLabs in terms of video quality.

Q: What are the recommended use cases?

The model is suitable for various applications including research on generative models, artistic content creation, educational tools, and commercial applications (with proper licensing). It's particularly effective for creating short animations, creative content, and design visualization.

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