--- title: Extend3D emoji: 🧩 colorFrom: blue colorTo: purple sdk: gradio sdk_version: 5.34.2 python_version: "3.10" app_file: app.py suggested_hardware: a10g-large tags: - 3d-generation - image-to-3d - gaussian-splatting - mesh short_description: "[CVPR 2026] Extend3D: Town-Scale 3D Generation" pinned: false ---

Extend3D: Town-scale 3D Generation

CVPR 2026

Seungwoo Yoon, Jinmo Kim, Jaesik Park
Seoul National University

![teaser](assets/images/teaser.png) ## 🛠 Preparation ### Environment - Linux x86-64 system - NVIDIA GPU with 24GB VRAM ($a=b=2$) - CUDA version ≥ 12.4 Larger scene generation may require more VRAM. ### Install ```bash conda create -n extend3d python=3.10 conda activate extend3d pip install -r requirements.txt ``` If your GPU does not support pytorch-2.4.0, follow instructions in [SETUP.md](./SETUP.md). ## 🚀 Usage ### Quick Start ```python from extend3d import Extend3D from PIL import Image import imageio from trellis.utils import render_utils, postprocessing_utils pipeline = Extend3D.from_pretrained("microsoft/TRELLIS-image-large").cuda() image = Image.open("assets/examples/0.png") output = pipeline.run(image) video = render_utils.render_video(output['gaussian'][0], r=1.6, resolution=1024)['color'] imageio.mimsave('sample_gs.mp4', video, fps=30) glb = postprocessing_utils.to_glb( output['gaussian'][0], output['mesh'][0], simplify=0.9, texture_size=1024 ) glb.export(os.path.join(args.output_dir, 'sample.glb')) ``` You may follow [example.py](./example.py) for detailed hyper-parameters. ### Gradio Demo ```bash python app.py ``` ## 📚 Citation ```bibtex @inproceedings{yoon2026extend3d, title = {Extend3D: Town-scale 3D Generation}, author = {Yoon, Seungwoo, and Kim, Jinmo, and Park, Jaesik}, booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference}, year = {2026} } ``` ## Acknowledgement This repository is based on the implementation from [Trellis](https://github.com/microsoft/TRELLIS/tree/442aa1e1afb9014e80681d3bf604e8d728a86ee7). We sincerely thank the authors for releasing their code. We also thank the anonymous reviewers for their insightful and constructive feedback.