Step-Video-TI2V
| Property | Value |
|---|---|
| Author | stepfun-ai |
| Paper | Technical Report |
| Model Repository | Hugging Face |
What is stepvideo-ti2v?
Step-Video-TI2V is a cutting-edge text-driven image-to-video generation model that transforms static images into dynamic videos. Released in March 2025, it represents a significant advancement in video generation technology, featuring a decoupled architecture for optimal GPU resource utilization.
Implementation Details
The model employs a sophisticated architecture that separates the text encoder, VAE decoding, and DiT components. This design choice optimizes GPU resource usage and enables parallel processing capabilities. The implementation supports various resolution options and can process videos with different frame counts efficiently.
- Supports parallel processing with 4 or 8 GPU configurations
- Handles high-resolution output (up to 768px × 768px × 102 frames)
- Achieves significant speed improvements with parallel processing (288s vs 1061s for same output)
- Implements configurable parameters for motion score, CFG scale, and time shift
Core Capabilities
- High-quality video generation from static images
- Text-driven control over video generation
- Efficient resource utilization through decoupled architecture
- Support for various resolution and frame count combinations
- Integration with ComfyUI for user-friendly implementation
Frequently Asked Questions
Q: What makes this model unique?
The model's decoupled architecture and parallel processing capabilities make it highly efficient for video generation, while maintaining high output quality. It can process various resolution and frame count combinations with optimized GPU utilization.
Q: What are the recommended use cases?
The model is ideal for applications requiring high-quality video generation from static images, such as content creation, animation, and visual effects. It's particularly suitable for environments with multiple GPU resources available.
