[CVPR 2024] Official PyTorch implementation of SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering
I would like to ask if I can only optimize the part I want. For example, I use SuperSplat and other tools to edit the ply scene generated by 3D GS, and then use SuGaR method to optimize and extract the Mesh.
This is the scene trained by 3D GS:
This is the scene after I edited it, which is the part of the mesh that I want to extract:
Can I use edited scenarios (point_cloud_sp.ply) instead of the original 3D GS-generated scenarios (point_cloud.ply) before using SugGaR for training?
Very good work, I got great results using SuGaR!
I would like to ask if I can only optimize the part I want. For example, I use SuperSplat and other tools to edit the ply scene generated by 3D GS, and then use SuGaR method to optimize and extract the Mesh.
This is the scene trained by 3D GS:
This is the scene after I edited it, which is the part of the mesh that I want to extract:
Can I use edited scenarios (point_cloud_sp.ply) instead of the original 3D GS-generated scenarios (point_cloud.ply) before using SugGaR for training?
I tried, but the results were not very good: