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+trained_models/tshirt/garment_wrinkles/model.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text

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+venv
+results
+assets/CMU/*
+assets/SMPL/*
+__pycache__

README.md

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+# Learning-Based Animation of Clothing for Virtual Try-On
+
+![Teaser](assets/images/teaser.jpg "Teaser image")
+
+[[Project website](https://dancasas.github.io/projects/LearningBasedVirtualTryOn/)] [[Dataset](https://github.com/isantesteban/vto-dataset)] [[Video](https://youtu.be/o2KJoAhEGg8)]
+
+## Abstract
+
+>This paper presents a learning-based clothing animation method for highly efficient virtual try-on simulation. Given a garment, we preprocess a rich database of physically-based dressed character simulations, for multiple body shapes and animations. Then, using this database, we train a learning-based model of cloth drape and wrinkles, as a function of body shape and dynamics. We propose a model that separates global garment fit, due to body shape, from local garment wrinkles, due to both pose dynamics and body shape. We use a recurrent neural network to regress garment wrinkles, and we achieve highly plausible nonlinear effects, in contrast to the blending artifacts suffered by previous methods. At runtime, dynamic virtual try-on animations are produced in just a few milliseconds for garments with thousands of triangles. We show qualitative and quantitative analysis of results.
+
+# Running the model
+
+**Requirements**: ```python3```, ```tensorflow-2.2.1```, ```numpy-1.18.5```, ```scipy-1.7.1```, ```chumpy-0.70```
+
+**Project structure**:
+```
+vto-learning-based-animation
+│
+└───assets 
+|    └─ images    
+|    └─ meshes    
+|    └─ CMU       # Not included, see instructions
+|    └─ SMPL      # Not included, see instructions
+| 
+└───rendering     # Code to render meshes 
+|
+└───src           # Code to run the model
+| 
+└───trained_models      
+│
+└───run_model.py
+```
+
+## Download human model
+
+1. Sign in into https://smpl.is.tue.mpg.de
+2. Download SMPL version 1.0.0 for Python 2.7 (10 shape PCs)
+3. Extract ```SMPL_python_v.1.0.0.zip``` and copy ```smpl/models/basicModel_f_lbs_10_207_0_v1.0.0.pkl``` in ```assets/SMPL```
+
+## Download animation sequences
+
+1. Sign in into https://amass.is.tue.mpg.de
+2. Download the body data for the CMU motions (SMPL+H model)
+3. Extract ```CMU.tar.bz2``` in ```assets/CMU```:  
+```sh
+tar -C assets/ -xf ~/Downloads/CMU.tar.bz2 CMU/ 
+```
+
+## Generate garment animation
+
+To generate the deformed garment meshes for a given sequence:
+
+```sh
+python run_model.py assets/CMU/07/07_02_poses.npz --export_dir results/07_02
+```
+
+
+# Rendering
+**Requirements**: ```blender-2.93```, ```ffmpeg```
+
+To render the meshes:
+
+```sh
+blender --background rendering/scene.blend --python rendering/render.py --path results/07_02
+```
+
+![Render](assets/images/render.gif "Video rendered by Blender")
+
+# Citation
+
+If you find this repository useful please cite our work:
+
+```
+@article {santesteban2019virtualtryon,
+    journal = {Computer Graphics Forum (Proc. Eurographics)},
+    title = {{Learning-Based Animation of Clothing for Virtual Try-On}},
+    author = {Santesteban, Igor and Otaduy, Miguel A. and Casas, Dan},
+    year = {2019},
+    ISSN = {1467-8659},
+    DOI = {10.1111/cgf.13643}
+}
+```
+