SGP23_AttPos4ShapeMatching

Paper at https://diglib.eg.org/handle/10.1111/cgf14912

Code based on the X-Transformers library by Lucidrains: https://github.com/lucidrains/x-transformers

Datasets, Utils and Testing from the transmatching code by GiovanniTRA: https://github.com/GiovanniTRA/transmatching

to test the trained model on FAUST1K, simply run:

python faust1k_ropeattn.py

to train a model, download the dataset folder from here, and then run:

python train_ropeattn.py

Citation

Please cite the following paper if you use the data or code in this repo.

@article{raganatoetalSGP2023,
journal = {Computer Graphics Forum},
title = {{Attention And Positional Encoding Are (Almost) All You Need For Shape Matching}},
author = {Raganato, Alessandro and Pasi, Gabriella and Melzi, Simone},
year = {2023},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.14912}
}