Stable Video Diffusion Image-to-Video
| Property | Value |
|---|---|
| Developer | Stability AI |
| License | Stable Video Diffusion Community |
| Paper | Research Paper |
| Training Resources | 200,000 A100 80GB hours |
What is stable-video-diffusion-img2vid?
Stable Video Diffusion (SVD) is a sophisticated latent diffusion model designed to transform static images into dynamic video sequences. Developed by Stability AI, this model can generate 14-frame video clips at an impressive resolution of 576x1024 pixels from a single input image. The model incorporates a specially fine-tuned f8-decoder for maintaining temporal consistency across frames.
Implementation Details
The model operates using a latent diffusion architecture and has been extensively trained with significant computational resources (approximately 200,000 A100 80GB hours). It features both standard frame-wise decoder capabilities and specialized temporal consistency mechanisms. The training process resulted in approximately 19,000kg CO2 eq. emissions and consumed about 64,000 kWh of energy.
- Generates 14-frame sequences at 576x1024 resolution
- Inference time: ~100s on A100 80GB GPU
- Includes built-in watermarking functionality
- Optimized for temporal consistency
Core Capabilities
- High-quality video generation from still images
- Temporal consistency maintenance
- Support for artistic and creative applications
- Research-focused functionality
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its ability to generate high-quality video sequences from single images while maintaining temporal consistency. Human evaluations have shown it to be preferred over competitors like GEN-2 and PikaLabs in terms of video quality.
Q: What are the recommended use cases?
The model is primarily intended for research purposes, including generative model research, safe deployment studies, bias investigation, and creative applications in education and design. Commercial use requires specific licensing from Stability AI.
