Instructions to use peaes/GeoWorld with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use peaes/GeoWorld with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("peaes/GeoWorld", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
GeoWorld: Providing Full-frame Geometry Features to Facilitate 3D Scene Generation
This repository contains the model weights for GeoWorld, presented in the paper GeoWorld: Providing Full-frame Geometry Features to Facilitate 3D Scene Generation.
Authors: Yuhao Wan, Lijuan Liu, Jingzhi Zhou, Zihan Zhou, Xuying Zhang, Dongbo Zhang, Shaohui Jiao, Qibin Hou, Ming-Ming Cheng
Project Page | Paper(arXiv) | Code
TL;DR: GeoWorld uses a two-stage video-generation pipeline with full-frame geometry features to produce high-fidelity image-to-3D scenes faster than prior methods (7.5× faster than Hunyuan-Voyager).
Usage
Please refer to the official GitHub repository for installation instructions.
Citation
@article{wan2025geoworld,
title={GeoWorld: Unlocking the Potential of Geometry Models to Facilitate High-Fidelity 3D Scene Generation},
author={Wan, Yuhao and Liu, Lijuan and Zhou, Jingzhi and Zhou, Zihan and Zhang, Xuying and Zhang, Dongbo and Jiao, Shaohui and Hou, Qibin and Cheng, Ming-Ming},
journal={arXiv preprint arXiv:2511.23191},
year={2025}
}