This repository contains the code of the paper "Partial-to-Partial Shape Matching with Geometric Consistency", V.Ehm, M.Gao, P. Roetzer, M. Eisenberger, D. Cremers, F. Bernard. CVPR 2024. It provides code to solve the partial-to-partial shape matching problem utilizing geometric consistency.

It consists of two main folders:

• processing (in Python): Preprocessing and Postprocessing of shapes.
• matlab: Matlab code to solve the partial-to-partial shape matching approach, which is based on [1,2,3].

Add a conda environment

conda create -n gc-ppsm python=3.8
conda activate gc-ppsm

Add additional requirements

pip install -r processing/requirements.txt

• YALMIP
• Matlab
• Gurobi (for Matlab)
• Run the setup_matlab() file (Adjust the path to the repo beforehand)

• Run processing/downsample_mesh.py to downsample the meshes from the data folder to low resolution
• Run matlab/call_main.m to solve the partial-to-partial shape matching problem on low resolution
• Run processsing/gen_high_res_mat.py to generate the high resolution solution based on the given low resolution solution

You can find the indices for the CUTS24 dataset here.

[1] Windheuser, T., Schlickwei, U., Schimdt, F. R., & Cremers, D. (2011, August). Large‐scale integer linear programming for orientation preserving 3d shape matching. In Computer Graphics Forum (Vol. 30, No. 5, pp. 1471-1480). Oxford, UK: Blackwell Publishing Ltd.

[2] Windheuser, T., Schlickewei, U., Schmidt, F. R., & Cremers, D. (2011, November). Geometrically consistent elastic matching of 3d shapes: A linear programming solution. In 2011 International Conference on Computer Vision (pp. 2134-2141). IEEE.

[3] P. Roetzer, P. Swoboda, D. Cremers, F. Bernard (2021). A Scalable Combinatorial Solver for Elastic Geometrically Consistent 3D Shape Matching. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2022