Stereo World Model: Camera-Guided Stereo Video Generation
Paper β’ 2603.17375 β’ Published β’ 11
How to use Yang-Tian/StereoWorld with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Yang-Tian/StereoWorld", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]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/
βββ StereoWorldModel/
β βββ transformer/
β βββ vae/
β βββ tokenizer/
β βββ text_encoder/
β βββ scheduler/
βββ StereoWorldFlexModel/
β βββ transformer/
β βββ vae/
β βββ tokenizer/
β βββ text_encoder/
β βββ scheduler/
βββ StereoWorldInpaintModel/
βββ transformer/
βββ vae/
βββ tokenizer/
βββ text_encoder/
βββ 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}
}