metadata
language:
- en
pipeline_tag: image-to-video
tags:
- video-generation
- image-to-video
- world-model
- robotics
- action-conditioned
- pytorch
library_name: pytorch
base_model:
- Wan-AI/Wan2.2-TI2V-5B
Boundless-World-Model
BWM: Physically consistent, action-conditioned video world model for robotic manipulation
Model Details
| Property | Value |
|---|---|
| Base Model | Wan2.2-TI2V-5B |
| Resolution | 480 x 640 |
| Frames | 81 frames |
| Control Signals | Robot action trajectories |
| Architecture | Trainable DiT + Action Encoder |
Usage
To use these weights, please refer to our GitHub repository.
Acknowledgements
This project builds upon the following open-source projects and benchmarks:
- Wan2.2: https://github.com/Wan-Video/Wan2.2
- DiffSynth-Studio: https://github.com/modelscope/DiffSynth-Studio
- WorldArena: https://github.com/tsinghua-fib-lab/WorldArena/
- ABot-PhysWorld: https://github.com/amap-cvlab/ABot-PhysWorld