This repo contains utility and visualization scripts related to the mesh reconstruction based on Gaussian splatting.
For SuGaR, there is a bash script for training a Gaussian splatting model
Please clone the repository of dn-splatter, and follow the installation instructions. The training script should be placed in the root directory of SuGaR.
Under notebooks, you can find a Jupyter notebook for SuGaR visualization and evaluation.
For dn-splatter, there are bash scripts for training a Gaussian splatting model and mesh extraction & evaluation.
Please clone the repository of dn-splatter, and follow the installation instructions. The scripts should be placed under the root directory of dn-splatter.
I would recommend applying a patch to avoid segfault when extracting mesh using gaussians method.
A Python evaluation script can be used to calculate two variants of Normalized Chamfer distance between a ground truth and reconstructed mesh.
It should be placed in the parent directory of dn-splatter and SuGaR.
Under notebooks, you can find a Jupyter notebook for object mask prediction using SAM2.