Deep Detail Enhancement for Any Garment
Deep-Detail-Enhancement-for-Any-Garment
This repository contains the implementation of Deep Detail Enhancment for Any Garment proposed in Eurographics 2021
Ref. to [http://geometry.cs.ucl.ac.uk/projects/2021/DeepDetailEnhance/paper_docs/DeepDetailEnhance.pdf]
We provide Google drive links for downloading the training data, the network checkpoint and two multi-layer garment models (Marvelouse Desigener):
./network_train_and_run
This folder contains the pytorch implemetation of deep detail enhancement network and the material classifier. In order to generalize our approach across different 2D parameterizations, we adopt a patch-based approach. Instead of operating with complete normal maps, we use patches cut from the normal maps as input and output of our network. If you want to retrain either of the two models, please first run “PatchPrepare.py” on the complete normal maps to generate