需先在 Hugging Face 接受 FLUX.1-dev 门控模型许可并 huggingface-cli login,否则模型无法下载;DA-2 需单独用 --no-deps 安装以避免版本冲突;mesh 模式需另装作者定制的 viser 才能正确显示,demo 默认在 localhost:8080 启动服务。

WorldGen
ZiYang-xieApache-2.0更新放缓秒级生成任意 3D 场景的生成模型,支持文本或图像输入,可用于快速搭建三维世界与场景重建。
🌍 WorldGen - Generate Any 3D Scene in Seconds
git clone --recursive https://github.com/ZiYang-xie/WorldGen.git
cd WorldGen
conda create -n worldgen python=3.11
conda activate worldgen
pip3 install torch torchvision
pip install .README 说明显存低于 24GB 时需开启 low_vram,低显存模式生成约占用 10GB 显存;代码按 cuda 可用性选择设备,未明确说明 CPU 可跑及支持的 GPU 厂商型号。
从文本或图片秒级生成可自由漫游的3D场景,适合游戏、仿真与VR环境搭建
秒级生成任意 3D 场景的生成模型,支持文本或图像输入,可用于快速搭建三维世界与场景重建。
核心能力
- 支持文本提示与图片两种输入生成3D场景
- 生成结果支持360°一致漫游并带闭环
- 可输出高斯泼溅或mesh两种场景格式
- 低显存模式约10GB显存即可生成
- 内置Viser在浏览器实时渲染任意视角
容易踩的坑
暂无 release 数据(可能没有发版,或尚未同步)。
用户点评
登录用户的真实使用记录,可按版本和硬件筛选还没有人点评。第一个说出真实体验的人最有价值。
WorldGen: Generate Any 3D Scene in Seconds
Author 👨💻: Ziyang Xie Contact Email 📧: [email protected]
Feel free to contact me for any questions or collaborations!
🌟 Introduction
🌏 WorldGen can generate 3D scenes in seconds from text prompts and images. It is a powerful tool for creating 3D environments and scenes for games, simulations, robotics, and virtual reality applications.
- Instant 3D Generation ⚡️ : Create full 3D scenes from input data in seconds
- 360° Free Exploration 🧭 : WorldGen supports free 360° consistent exploration of the generated 3D scene with loop closure.
- Diverse Scenes Support 🌈 : WorldGen supports both indoor and outdoor scenes, both realistic and unrealistic scenes in any style.
- Flexible Rendering 📸 : WorldGen supports rendering at any resolution with any camera setting and trajectory in real-time.
Two lines of code to generate a 3D scene in seconds
# Use our API to generate a 3D scene
worldgen = WorldGen()
worldgen.generate_world("<TEXT PROMPT to describe the scene>")
Text-to-Scene Generation
Image-to-Scene Generation
News and TODOs
-
04.12.2026🔧 [Improved Sharp] Rework ml-sharp pipeline: use cubemap depth to align Sharp's per-face gaussians for better global consistency. Reduced from 8+ views to 6 cubemap faces. -
04.11.2026🔄 [Updated Depth] Replace UniK3D with DA-2 for better 360° depth estimation. -
03.17.2026🔧 [Improved Quality] Improve the GS quality by fixing the project scale issue. Make ml-sharp dependency optional. -
01.10.2026🔥 [New feature] Add support for ml-sharp (modified to work on 360 images) for better GS generation (Currently in experimental mode) -
05.10.2025🤖 Add support for low-vram generation (Only use ~10GB VRAM for generation). -
04.26.2025📄 New Relase a project page for WorldGen -
04.22.2025🏡 Add support for mesh scene generation (Should give better results than splat) -
04.21.2025🎉 Opensource the WorldGen codebase -
04.19.2025🖼️ Add support for image-to-scene generation -
04.17.2025📝 Add support for text-to-scene generation - Release technical report and video
- Support better background inpainting (Invisible region inpainting)
📦 Installation
Getting started with WorldGen is simple!
# Clone the repository
git clone --recursive https://github.com/ZiYang-xie/WorldGen.git
cd WorldGen
# Create a new conda environment
conda create -n worldgen python=3.11
conda activate worldgen
# Install torch and torchvision (with GPU support)
pip3 install torch torchvision
# Install worldgen
pip install .
# Install DA-2 (360 depth estimation) -- use --no-deps to avoid version conflicts
pip install git+https://github.com/EnVision-Research/DA-2.git#subdirectory=src --no-deps
# Install pytorch3d dependencies
pip install git+https://github.com/facebookresearch/pytorch3d.git --no-build-isolation
# 🔥 [New feature]: If you want to use the ml-sharp experimental feature, you need to install the ml-sharp dependencies
pip install -e submodules/ml-sharp
# You should also accept the license of the gated model (FLUX.1-dev).
# https://huggingface.co/black-forest-labs/FLUX.1-dev
# Login to Hugging Face and accept the license.
# huggingface-cli login
🕹️ Quick Start / Demos
We provide a demo script to help you quickly get started and visualize the 3D scene in a web browser. The script is powered by Viser.
# Generate a 3D scene from a text prompt
python demo.py -p "A beautiful landscape with a river and mountains"
# Indoor scene example
python demo.py -p "A well-designed cozy bedroom"
# 🔥 New feature: Generate a 3D scene using the ml-sharp experimental feature (It may produce better results than the default mode)
python demo.py -p "<TEXT PROMPT to describe the scene>" --use_sharp
# Generate a 3D scene from an image
python demo.py -i "path/to/your/image.jpg" -p "<Optional: TEXT PROMPT to describe the scene>" --use_sharp
# Generate a 3D scene in mesh mode
# Make sure you installed my customized viser to correctly visualize the mesh without backface culling
# pip install git+https://github.com/ZiYang-xie/viser.git
python demo.py -p "A beautiful landscape with a river and mountains" --return_mesh
After running the demo script, A local viser server will be launched at http://localhost:8080, where you can explore the generated 3D scene in real-time.
🎮 Advanced Usage
WorldGen API
Quick start with WorldGen (mode in t2s or i2s) and generate your first 3D scene in seconds:
- 📝 Text to Scene: Generate a 3D scene from a text prompt
# Example using the Python API
from worldgen import WorldGen
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
worldgen = WorldGen(mode="t2s", device=device, low_vram=False) # Set low_vram to True if your GPU VRAM is less than 24GB.
splat = worldgen.generate_world("<TEXT PROMPT to describe the scene>")
splat.save("path/to/your/output.ply") # Save splat file as a .ply file, which can be loaded and visualized using a standard gaussian splatting viewer
- 🖼️ Image to Scene: Generate a 3D scene from an image
worldgen = WorldGen(mode="i2s", device=device, low_vram=False) # Set low_vram to True if your GPU VRAM is less than 24GB.
image = Image.open("path/to/your/image.jpg")
splat = worldgen.generate_world(
image=image,
prompt="<Optional: TEXT PROMPT to describe the image and the scene>",
)
- 🏡 Generate a 3D scene in mesh mode
mesh = worldgen.generate_world("<TEXT PROMPT to describe the scene>", return_mesh=True)
o3d.io.write_triangle_mesh("path/to/your/output.ply", mesh) # Save mesh as a .ply file
[!Tip] We also support background inpainting for better scene generation, but it's currently an experimental feature, which may not work for all scenes.
It can be enabled by settingWorldGen(inpaint_bg=True).
# If want to use background inpainting feature, install iopaint
pip install iopaint --no-dependencies
Free-viewpoint Exploration in 3D Scene
[!Note] WorldGen internally support generating a 3D scene from a 360° panorama image 📸, which related to how WorldGen works: You can try it out if you happen to have a 360° panorama (equirectangular) image. Aspect ratio of the panorama image should be 2:1.
pano_image = Image.open("path/to/your/pano_image.jpg")
splat = worldgen._generate_world(pano_image=pano_image)
⭐️ Star History
Give a star to WorldGen if you like it!
📚 Citation
If you find this project useful, please consider citing it as follows:
@misc{worldgen2025ziyangxie,
author = {Ziyang Xie},
title = {WorldGen: Generate Any 3D Scene in Seconds},
year = {2025},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/ZiYang-xie/WorldGen}},
}
🤝 Acknowledgements
This project is built on top of the follows, please consider citing them if you find them useful:
Some of the core methods and ideas in this project are inspired by the following projects, special thanks to them:
- WonderWorld [RGBD to GS conversion]
- WorldSheet [Mesh Generation]