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Yang-Tian/StereoWorld
StereoWorld is a machine learning model from Yang-Tian. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for diffusers. The card lists the license as apache-2.0.
Official model weights for StereoWorld: Camera-Guided Stereo Video Generation.
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Updated Aug 21, 2026
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From the Hugging Face model README
Official model weights for StereoWorld: Camera-Guided Stereo Video Generation.
| Directory | Model | Description |
|---|---|---|
StereoWorldModel/ | Fixed-Baseline Stereo | Generates side-by-side stereo video with a configurable but fixed stereo baseline. Use --use_raymap during inference. |
StereoWorldFlexModel/ | Flexible Stereo | Provides independent left/right camera control with converging, horizontal-offset, depth-offset, and height-offset right-camera modes. |
StereoWorldInpaintModel/ | Fixed-Left View Inpainting | Generates a right-view video from an input left-view video while locking the left-video latents during sampling. |
StereoWorldModel/)A binocular teacher model for standard stereo video generation with consistent disparity and a fixed baseline.
StereoWorldFlexModel/)A multi-view world model with independently controlled left and right camera trajectories and four flexible right-camera modes.
StereoWorldInpaintModel/)Generates a right-view video from an input left-view video with camera-guided fixed-left view inpainting.
huggingface-cli download Yang-Tian/StereoWorld --local-dir weights
huggingface-cli download Yang-Tian/StereoWorld \
--include "StereoWorldModel/*" \
--local-dir weights
huggingface-cli download Yang-Tian/StereoWorld \
--include "StereoWorldFlexModel/*" \
--local-dir weights
huggingface-cli download Yang-Tian/StereoWorld \
--include "StereoWorldInpaintModel/*" \
--local-dir weights
StereoWorld/
├── StereoWorldModel/
│ ├── transformer/
│ ├── vae/
│ ├── tokenizer/
│ ├── text_encoder/
│ └── scheduler/
├── StereoWorldFlexModel/
│ ├── transformer/
│ ├── vae/
│ ├── tokenizer/
│ ├── text_encoder/
│ └── scheduler/
└── StereoWorldInpaintModel/
├── transformer/
├── vae/
├── tokenizer/
├── text_encoder/
└── scheduler/
Clone the StereoWorld code repository and install its dependencies before running inference:
git clone https://github.com/SunYangtian/StereoWorld.git
cd StereoWorld
pip install -r requirements.txt
python3 inference.py \
--pipeline_dir weights/StereoWorldModel \
--use_raymap \
--eval_json ExpData/demo_custom_eval.json
python3 inference_flex.py \
--pipeline_dir weights/StereoWorldFlexModel \
--eval_json ExpData/flex_demo_custom_eval.json
python3 inference_view_inpainting.py \
--pipeline_dir weights/StereoWorldInpaintModel \
--eval_json ExpData/view_inpaint_eval.json
Outputs for the bundled examples are organized under output_view_inpaint/caseN/.
See the GitHub repository for installation details and further inference options.
@article{sun2026stereo,
title={Stereo World Model: Camera-Guided Stereo Video Generation},
author={Sun Yang-Tian and Huang Zehuan and Niu Yifan and Ma Lin and Cao Yan-Pei and Ma Yuewen and Qi Xiaojuan},
journal={arXiv preprint arXiv:2603.17375},
year={2026}
}