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MorphAny3D

[CVPR 2026] Official repo of "MorphAny3D: Unleashing the Power of Structured Latent in 3D Morphing“

Install / Use

/learn @XiaokunSun/MorphAny3D
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

<div align="center">

[CVPR 2026] MorphAny3D: Unleashing the Power of Structured Latent in 3D Morphing

<div> <a href="https://xiaokunsun.github.io"><strong>Xiaokun Sun</strong></a><sup>1</sup>, <a href="https://zcai0612.github.io"><strong>Zeyu Cai</strong></a><sup>1</sup>, <a href="https://ha0tang.github.io"><strong>Hao Tang</strong></a><sup>2</sup>, <a href="https://tyshiwo.github.io/index.html"><strong>Ying Tai</strong></a><sup>1</sup>, <a href="https://scholar.google.com.hk/citations?user=6CIDtZQAAAAJ"><strong>Jian Yang</strong></a><sup>1</sup>, <a href="https://jessezhang92.github.io"><strong>Zhenyu Zhang</strong></a><sup>1*</sup> </div> <div> <sup>1</sup><strong>Nanjing University</strong> &nbsp;&nbsp; <sup>2</sup><strong>Peking University</strong> </div> <div> <sup>*</sup><strong>Corresponding Author</strong> </div> <br>

ArXiv Project Page Blog <br> <img src="assets/teaser.png" alt="Teaser" width="100%">

</div>

🔨 Installation

Tested on Ubuntu 20.04, Python 3.10, NVIDIA A6000, CUDA 11.8, and PyTorch 2.4.0. Follow the steps below to set up the environment.

  1. Clone the repo:

    git clone https://github.com/XiaokunSun/MorphAny3D.git
    cd MorphAny3D
    
  2. Setup the environment:

    As MorphAny3D builds upon TRELLIS. You can find more details about the dependencies in the TRELLIS repository.

    bash ./setup.sh --new-env --basic --xformers --flash-attn --diffoctreerast --spconv --mipgaussian --kaolin --nvdiffrast
    conda install https://anaconda.org/pytorch3d/pytorch3d/0.7.8/download/linux-64/pytorch3d-0.7.8-py310_cu118_pyt240.tar.bz2 # Note: Please ensure the pytorch3d version matches your Python, CUDA and Torch versions
    
  3. Download pretrained models:

    We do not modify the pretrained models of TRELLIS. The weights will be automatically downloaded when you run:

    TrellisImageTo3DPipeline.from_pretrained("microsoft/TRELLIS-image-large")
    

    Optionally, you can manually download the weights from HuggingFace and change the path in the above command to the local path.

    TrellisImageTo3DPipeline.from_pretrained("path/to/local/directory")
    

🕺 Inference

# 3D Morphing
python ./example_3Dmorphing.py

🪄 Application

# Disentangled 3D Morphing
python ./example_disentangled_3Dmorphing.py
# Dual-Target 3D Morphing
python ./example_dual_target_3Dmorphing.py
# 3D Style Transfer
python ./example_3Dstyle_transfer.py

💖 Acknowledgements

This code builds upon TRELLIS. We sincerely thank the authors for their great work and open-sourcing the code.

📚 Citation

If you find our work helpful for your research, please consider starring this repository ⭐ and citing our work:

@inproceedings{sun2026morphany3d,
  title={MorphAny3D: Unleashing the Power of Structured Latent in 3D Morphing},
  author={Sun, Xiaokun and Cai, Zeyu and and Tang, Hao and Tai, Ying and Yang, Jian and Zhang, Zhenyu},
  booktitle={CVPR},
  year={2026}
}

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Audited on Apr 5, 2026

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