DynamicNeuralGarments
Introduction
This repository contains the implemetation of Dynamic Nerual Garments proposed in Siggraph Asia 2021.
./GarmentMotionRenderer
This folder contains the pytorch implementation of the rendering network. 
You can play with the code by running "run.py" after downloading data and checkpoint from here. You will get the similar results as shown below by respectively running the check point from multilayers, tango, twolayers
In case you want to retrain the network, you can download the training data from here. We provide the 3D meshes of coarse garment, and the target garments including multilayers, tango, and twolayers. You will first run the blender project to generate the groundtruth rendering, background rendering and save the corresponding camera poses. Next, you need to compute the texture sampling map by referring to the code in ./PixelSample. After gathering all needed data, you can give a shot at "train.py".
./PixelSample
This folder contains the code to generate texture sampling map. The C++ code relies on OpenCV, and Embree.
./blenderScript
This folder contains python scripts for blender.
Citation
If you use our code or model, please cite our paper:
@article{zhang2021dynamic, title={Dynamic Neural Garments}, author={Zhang, Meng and Ceylan, Duygu and Wang, Tuanfeng and Mitra, Niloy J}, journal={arXiv preprint arXiv:2102.11811}, year={2021} }
101 Jan 1, 2023
54 Dec 6, 2022
49 Oct 31, 2022
61 Nov 27, 2022
23 Dec 9, 2022
258 Jan 2, 2023
203 Jan 5, 2023
194 Dec 6, 2022
270 Dec 30, 2022
5 Oct 22, 2021
150 Dec 7, 2022
33 Dec 18, 2022
30 Dec 24, 2022
249 Jan 8, 2023
59 Nov 24, 2022
40 Dec 13, 2022
32 Jan 5, 2023
118 Dec 27, 2022