Welcome to the world of SIFU, a groundbreaking method designed to reconstruct high-quality 3D models of clothed humans using just a single image. This innovative approach is tailored for a variety of practical applications, including 3D printing, scene creation, and animation.

What Makes SIFU Unique?

SIFU stands out due to its novel components:

• Side-view Conditioned Implicit Function: This feature enhances the extraction of geometric details and improves overall accuracy.
• 3D Consistent Texture Refinement: It significantly elevates texture quality, making it easier to edit textures via text-to-image diffusion models.
• Complex Pose Handling: This system excels even when human models are in complex positions or wearing loose clothing.

Installation Guide

Ready to dive into the world of SIFU? Here’s a simple installation guide to get you started.

• Ensure your system runs on Ubuntu 18 or 20 with CUDA 11.6, 11.7, or 11.8 and a GPU Memory of 16GB.
• You will need Python 3.8 and PyTorch 1.13.0. You can find installation instructions here.

Step-by-step Installation

• Install conda or miniconda:

sudo apt-get update
sudo apt-get upgrade -y
sudo apt-get install unzip libeigen3-dev ffmpeg build-essential nvidia-cuda-toolkit
mkdir -p ~/miniconda3
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm -rf ~/miniconda3/miniconda.sh
~/miniconda3/bin/conda init bash
~/miniconda3/bin/conda init zsh
bash

• Clone the SIFU repository:

git clone https://github.com/River-Zhang/SIFU.git
sudo apt-get install libeigen3-dev ffmpeg
cd SIFU
conda env create -f environment.yaml
conda activate sifu
pip install -r requirements.txt

• Download the necessary checkpoints and data:

Please download the checkpoint and place it in .data/ckpt

• Follow the instructions at ICON’s documentation for additional data.

Running Inference

Once you have successfully installed SIFU, running inference is straightforward:

bash
python -m apps.infer -cfg .configs/sifu.yaml -gpu 0 -in_dir .examples -out_dir .results -loop_smpl 100 -loop_cloth 200 -hps_type pixie

Applications of SIFU

SIFU opens new doors in various fields:

• Scene Building: Create immersive environments for games and simulations.
• 3D Printing: Transform 3D models into tangible products.
• Texture Editing: Seamlessly modify textures in your 3D models.
• Animation: Bring characters to life with realistic movements.
• In-the-wild Reconstruction: Capture everyday scenarios with stunning realism.

Troubleshooting Tips

If you encounter issues during installation or inference, try the following:

• Ensure that your system meets all specified requirements, especially regarding GPU capabilities.
• Check that all necessary dependencies are properly installed and configured.
• Consult the documentation and community forums for guidance.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.