GTR: Improving Large 3D Reconstruction Models through Geometry and Texture Refinement

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Installation

We recommend using Python>=3.10, PyTorch==2.7.0, and CUDA>=12.4.

conda create --name gtr python=3.10
conda activate gtr
pip install -U pip

pip install torch==2.7.0 torchvision==0.22.0 torchmetrics==1.2.1 --index-url https://download.pytorch.org/whl/cu124
pip install -U xformers --index-url https://download.pytorch.org/whl/cu124

pip install -r requirements.txt

How to Use

Please download model checkpoint from here, and then put it under the ckpts/ directory.

We provide multiview grid data examples under ./examples/ generated using Zero123++. Our inference script loads pretrained checkpoint, runs fast texture refinement, reconstructs the textured mesh from multiview grid data and exports the mesh. There will be 3 files in the output folder, including exported mesh in .obj format, rotating gif visuals of mesh and rotating gif visuals of NeRF.

To infer on multiview data from other sources, simply change camera parameters here accordingly to match the multiview data.

# Preprocessing
python3 scripts/prepare_mv.py --in_dir ./examples/cute_horse.png --out_dir ./examples/cute_horse

# Inference
python3 scripts/inference.py --ckpt_path ckpts/full_checkpoint.pth --in_dir ./examples/cute_horse --out_dir ./outputs/cute_horse