Simulated garment dataset for virtual try-on

Overview

Simulated garment dataset for virtual try-on

This repository contains the dataset used in the following papers:

  • Self-Supervised Collision Handling via Generative 3D Garment Models for Virtual Try-On (CVPR 2021) [Project website] [Video]

  • Learning-Based Animation of Clothing for Virtual Try-On (Eurographics 2019) [Project website] [Video]

Dataset

Teaser

The data is generated used a modified version of ARCSim and sequences from the CMU Motion Capture Database converted to SMPL format in SURREAL. Each simulated sequence is stored as a .pkl file that contains the following data:

Key Description Dimension
shapes SMPL shape coefficients [num_frames, 10]
poses SMPL pose coefficients [num_frames, 75]
vertices Vertices of the simulated garment [num_frames, num_vertices, 3]
faces Faces of the garment [num_faces, 3]
sequence Sequence identifier
subject Subject identifier
conf ARCSim configuration

Extract meshes

Requirements: python3, numpy-1.21.3

To extract the simulated garment meshes as .obj run the following script:

python extract_meshes.py tshirt/simulations/tshirt_shape00_01_01.pkl

Citation

If you find this dataset useful please cite our work:

@article {santesteban2021garmentcollisions,
    journal = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    title = {{Self-Supervised Collision Handling via Generative 3D Garment Models for Virtual Try-On}},
    author = {Santesteban, Igor and Thuerey, Nils and Otaduy, Miguel A and Casas, Dan},
    year = {2021}
}
@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}
}
You might also like...
A 35mm camera, based on the Canonet G-III QL17 rangefinder, simulated in Python.
A 35mm camera, based on the Canonet G-III QL17 rangefinder, simulated in Python.

c is for Camera A 35mm camera, based on the Canonet G-III QL17 rangefinder, simulated in Python. The purpose of this project is to explore and underst

A framework for analyzing computer vision models with simulated data

3DB: A framework for analyzing computer vision models with simulated data Paper Quickstart guide Blog post Installation Follow instructions on: https:

"Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback"

This is code repo for our EMNLP 2017 paper "Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback", which implements the A2C algorithm on top of a neural encoder-decoder model and benchmarks the combination under simulated noisy rewards.

Trained on Simulated Data, Tested in the Real World
Trained on Simulated Data, Tested in the Real World

Trained on Simulated Data, Tested in the Real World

PINN Burgers - 1D Burgers equation simulated by PINN

PINN(s): Physics-Informed Neural Network(s) for Burgers equation This is an impl

Checkout some cool self-projects you can try your hands on to curb your boredom this December!

SoC-Winter Checkout some cool self-projects you can try your hands on to curb your boredom this December! These are short projects that you can do you

Try out deep learning models online on Google Colab

Try out deep learning models online on Google Colab

 VOGUE: Try-On by StyleGAN Interpolation Optimization
VOGUE: Try-On by StyleGAN Interpolation Optimization

VOGUE is a StyleGAN interpolation optimization algorithm for photo-realistic try-on. Top: shirt try-on automatically synthesized by our method in two different examples.

Official Implementation and Dataset of
Official Implementation and Dataset of "PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask and Group-Level Consistency", CVPR 2021

Portrait Photo Retouching with PPR10K Paper | Supplementary Material PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask an

Owner
null
Code for "ShineOn: Illuminating Design Choices for Practical Video-based Virtual Clothing Try-on", accepted at WACV 2021 Generation of Human Behavior Workshop.

ShineOn: Illuminating Design Choices for Practical Video-based Virtual Clothing Try-on [ Paper ] [ Project Page ] This repository contains the code fo

Andrew Jong 97 Dec 13, 2022
Official PyTorch implementation of "VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization" (CVPR 2021)

VITON-HD — Official PyTorch Implementation VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization Seunghwan Choi*1, Sunghyun Pa

Seunghwan Choi 250 Jan 6, 2023
Official code for ICCV2021 paper "M3D-VTON: A Monocular-to-3D Virtual Try-on Network"

M3D-VTON: A Monocular-to-3D Virtual Try-On Network Official code for ICCV2021 paper "M3D-VTON: A Monocular-to-3D Virtual Try-on Network" Paper | Suppl

null 109 Dec 29, 2022
(ICCV 2021) Official code of "Dressing in Order: Recurrent Person Image Generation for Pose Transfer, Virtual Try-on and Outfit Editing."

Dressing in Order (DiOr) ?? [Paper] ?? [Webpage] ?? [Running this code] The official implementation of "Dressing in Order: Recurrent Person Image Gene

Aiyu Cui 277 Dec 28, 2022
Official PyTorch implementation of "RMGN: A Regional Mask Guided Network for Parser-free Virtual Try-on" (IJCAI-ECAI 2022)

RMGN-VITON RMGN: A Regional Mask Guided Network for Parser-free Virtual Try-on In IJCAI-ECAI 2022(short oral). [Paper] [Supplementary Material] Abstra

null 27 Dec 1, 2022
This repository contains the implementation of Deep Detail Enhancment for Any Garment proposed in Eurographics 2021

Deep-Detail-Enhancement-for-Any-Garment Introduction This repository contains the implementation of Deep Detail Enhancment for Any Garment proposed in

null 40 Dec 13, 2022
AI Virtual Calculator: This is a simple virtual calculator based on Artificial intelligence.

AI Virtual Calculator: This is a simple virtual calculator that works with gestures using OpenCV. We will use our hand in the air to click on the calc

Md. Rakibul Islam 1 Jan 13, 2022
Users can free try their models on SIDD dataset based on this code

SIDD benchmark 1 Train python train.py If you want to train your network, just modify the yaml in the options folder. 2 Validation python validation.p

Yuzhi ZHAO 2 May 20, 2022
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)

scikit-opt Swarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm,A

郭飞 3.7k Jan 3, 2023
A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.

Object Pose Estimation Demo This tutorial will go through the steps necessary to perform pose estimation with a UR3 robotic arm in Unity. You’ll gain

Unity Technologies 187 Dec 24, 2022