Add image-to-3d pipeline tag and improve model card
Browse filesHi, I'm Niels from the Hugging Face community science team.
I've opened this PR to add the `pipeline_tag: image-to-3d` to your model card. This metadata is essential for ensuring your model is correctly indexed and discoverable by users interested in 3D generation on the Hugging Face Hub.
I have also updated the model card to include the "Getting Started" and "Usage" sections from your GitHub README, making it easier for users to understand how to run the model.
README.md
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---
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license: other
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license_name: pixal3d-license
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license_link: LICENSE
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extra_gated_eu_disallowed: true
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--
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<a href="https://
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<a href="https://huggingface.co/TencentARC/Pixal3D"><img src=https://img.shields.io/badge/%F0%9F%A4%97%
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<a href="https://
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</
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- **May 2026**: Release
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- **
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```
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@article{li2026pixal3d,
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title = {Pixal3D: Pixel-Aligned 3D Generation from Images},
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author = {Li, Dong-Yang and Zhao, Wang and Chen, Yuxin and Hu, Wenbo and Guo, Meng-Hao and Zhang, Fang-Lue and Shan, Ying and Hu, Shi-Min},
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journal = {arXiv preprint arXiv:2605.10922},
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year = {2026}
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}
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```
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---
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license: other
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license_name: pixal3d-license
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license_link: LICENSE
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extra_gated_eu_disallowed: true
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pipeline_tag: image-to-3d
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---
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<div align="center">
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# Pixal3D: Pixel-Aligned 3D Generation from Images
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<h3>SIGGRAPH 2026</h3>
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[Dong-Yang Li](https://ldyang694.github.io/)¹ · [Wang Zhao](https://thuzhaowang.github.io/)²* · [Yuxin Chen](https://orcid.org/0000-0002-7854-1072)² · [Wenbo Hu](https://wbhu.github.io/)² · [Meng-Hao Guo](https://menghaoguo.github.io/)¹ · [Fang-Lue Zhang](https://fanglue.github.io/)³ · [Ying Shan](https://www.linkedin.com/in/YingShanProfile)² · [Shi-Min Hu](https://cg.cs.tsinghua.edu.cn/shimin.htm)¹✉
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¹Tsinghua University (BNRist) ²Tencent ARC Lab ³Victoria University of Wellington
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*Project lead ✉Corresponding author
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</div>
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<div align="center">
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<a href="https://ldyang694.github.io/projects/pixal3d/"><img src=https://img.shields.io/badge/Project%20Page-333399.svg?logo=googlehome height=22px></a>
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<a href="https://huggingface.co/spaces/TencentARC/Pixal3D"><img src=https://img.shields.io/badge/%F0%9F%A4%97%20Demo-276cb4.svg height=22px></a>
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<a href="https://github.com/TencentARC/Pixal3D"><img src=https://img.shields.io/badge/Code-Github-black.svg?logo=github height=22px></a>
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<a href="https://arxiv.org/abs/2605.10922"><img src=https://img.shields.io/badge/Arxiv-b5212f.svg?logo=arxiv height=22px></a>
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</div>
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**Pixal3D** generates high-fidelity 3D assets from a single image. Unlike previous methods that loosely inject image features via attention, Pixal3D explicitly lifts pixel features into 3D through back-projection, establishing direct pixel-to-3D correspondences. This enables near-reconstruction-level fidelity with detailed geometry and PBR textures.
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---
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## ✨ News
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- **May 2026**: Release the improved version based on [Trellis.2](https://github.com/microsoft/TRELLIS.2) backbone. 💪
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- **May 2026**: Release inference code and online demo. 🤗
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- **Apr 2026**: Our paper is accepted to SIGGRAPH 2026! 🎉
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## 📌 Branches
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| Branch | Description |
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|--------|-------------|
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| `main` | **Latest version** — improved implementation based on [Trellis.2](https://github.com/microsoft/TRELLIS.2) backbone with better performance. |
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| `paper` | **Paper version** — original implementation based on [Direct3D-S2](https://github.com/DreamTechAI/Direct3D-S2), corresponding to results reported in our SIGGRAPH 2026 paper. |
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> If you want to reproduce the results in our paper, please switch to the `paper` branch.
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## 🎮 Try It Online
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You can try Pixal3D directly in your browser without any installation via our Hugging Face Gradio demo:
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👉 [**Launch Demo**](https://huggingface.co/spaces/TencentARC/Pixal3D)
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## 🚀 Getting Started
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### Installation
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#### Step 1: Follow TRELLIS.2 Installation
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Please first follow the installation guide of [TRELLIS.2](https://github.com/microsoft/TRELLIS.2) to set up the base environment.
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#### Step 2: Install Additional Dependencies
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```bash
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pip install -r requirements.txt
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```
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#### Step 3: Install utils3d
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```bash
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pip install https://github.com/LDYang694/Storages/releases/download/20260430/utils3d-0.0.2-py3-none-any.whl
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```
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### Usage
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#### Inference
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Generate a GLB mesh from a single image:
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```bash
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python inference.py --image assets/test_image/0.png --output ./output.glb
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```
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### Web Demo
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We provide a Gradio web demo for Pixal3D, which allows you to generate 3D meshes from images interactively.
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```bash
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python app.py
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```
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## 🤗 Acknowledgements
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This project is heavily built upon [Trellis.2](https://github.com/microsoft/TRELLIS.2) and [Direct3D-S2](https://github.com/DreamTechAI/Direct3D-S2). We also thank the following repos for their great contributions: [Trellis](https://github.com/microsoft/TRELLIS).
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## 📄 Citation
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If you find this work useful, please consider citing:
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```bibtex
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@article{li2026pixal3d,
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title = {Pixal3D: Pixel-Aligned 3D Generation from Images},
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author = {Li, Dong-Yang and Zhao, Wang and Chen, Yuxin and Hu, Wenbo and Guo, Meng-Hao and Zhang, Fang-Lue and Shan, Ying and Hu, Shi-Min},
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journal = {arXiv preprint arXiv:2605.10922},
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year = {2026}
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}
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```
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