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YouDream: Generating Anatomically Controllable Consistent Text-to-3D Animals

Sandeep Mishra<sup>✝︎</sup>, Oindrila Saha<sup>✝︎</sup>, Alan C. Bovik
Accepted at NeurIPS 2024


<h3 align="center"> <a href="https://arxiv.org/abs/2406.16273v1">[arXiv]</a> | <a href="https://youdream3d.github.io">[Project Page]</a> </h3>

Unseen Animal Generation

Anatomically Controlled 3D Outputs


Overview

YouDream introduces a novel approach for generating 3D animal models with anatomically accurate control, ensuring consistency and detail across generated outputs. This work combines text-to-3D generation with precise anatomical structures to cater to tasks requiring high-quality 3D assets in research and industry.


Git Log

To-Do List


Code Documentation

Installation

  1. Clone the repository:
    git clone https://github.com/YouDream3D/YouDream.git
    cd YouDream
    
  2. Create and activate the conda environment:
    conda create -n youdream python=3.9 -y
    conda activate youdream
    
  3. Install dependencies:
    conda install pytorch=1.13.0 torchvision pytorch-cuda=11.6 -c pytorch -c nvidia
    conda install -c iopath iopath
    conda install pytorch3d -c pytorch3d
    pip3 install -r requirements.txt
    
  4. Download the Animal Pose ControlNet Checkpoint: Visit the Hugging Face model page to download the animal_pose_controlnet checkpoint. Place the downloaded checkpoint folder: "animal_pose_controlnet" in the root directory of YouDream.

Running the Code

  1. Run the shell scripts to generate 3D models:
    ./run_all_tiger.sh 
    

Citation

If you find this work useful in your research or projects, please cite:

@article{mishra2024youdream,
  title={YouDream: Generating Anatomically Controllable Consistent Text-to-3D Animals},
  author={Mishra, Sandeep and Saha, Oindrila and Bovik, Alan C},
  journal={arXiv preprint arXiv:2406.16273},
  year={2024}
}

Acknowledgements

Our Code is based on DreamWaltz. We thank the DreamWaltz contributors for making the code available.

<sup>✝︎</sup> Equal contribution.