Implementation for the paper SMPLicit: Topology-aware Generative Model for Clothed People (CVPR 2021)

Related tags

Deep LearningSMPLicit
Overview

SMPLicit: Topology-aware Generative Model for Clothed People

[Project] [arXiv]

License

Software Copyright License for non-commercial scientific research purposes. Please read carefully the terms and conditions and any accompanying documentation before you download and/or use the SMPLicit model, data and software, (the "Model & Software"), including 3D meshes, blend weights, blend shapes, textures, software, scripts, and animations. By downloading and/or using the Model & Software (including downloading, cloning, installing, and any other use of this github repository), you acknowledge that you have read these terms and conditions, understand them, and agree to be bound by them. If you do not agree with these terms and conditions, you must not download and/or use the Model & Software. Any infringement of the terms of this agreement will automatically terminate your rights under this License.

Installation

Follow these commands to install SMPLicit in your environment. The required libraries are standard, with the possible exception of Kaolin which requires a particular version to run with the current code.

  • git clone https://github.com/ecorona/SMPLicit

  • cd SMPLicit

  • Install the dependencies listed in requirements.txt:

    • pip install -r requirements.txt
  • In particular, we use Kaolin v0.1 (see installation command) which should be easy to install. However, if you want to use a later version, you might need to update the import to TriangleMesh in SMPLicit/SMPLicit.py

  • Download the SMPL model from here and place it in SMPLicit/utils/

To be able to import and use SMPLicit in another project, just use run python setup.py install in the main folder.

Usage

To check that everything is going well, run one of the test scripts under the examples folder. The first example will just show a simple T-Shirt on a standard shaped SMPL and visualize it using trimesh, to make sure everything is working.

cd examples/
python example.py

SMPLicit can represent clothes of different types, so the following example will also add lower-body clothes, hair and shoes into the example:

python example_fullbody.py

And finally one can interpolate between clothes of different types. For instance, moving between a jacket, tops, short or long sleeved T-Shirts. The following script will generate object meshes that represent these clothes and will be saved in interpolation/, below the main folder.

python interpolate.py

Citation

If you find the code useful, please cite:

@inproceedings{corona2021smplicit,
    Author = {Enric Corona and Albert Pumarola and Guillem Aleny{\`a} and Pons-Moll, Gerard and Moreno-Noguer, Francesc},
    Title = {SMPLicit: Topology-aware Generative Model for Clothed People},
    Year = {2021},
    booktitle = {CVPR},
}
Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.

mtomo Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation.

Katsuya Hyodo 24 Mar 02, 2022
Using deep learning to predict gene structures of the coding genes in DNA sequences of Arabidopsis thaliana

DeepGeneAnnotator: A tool to annotate the gene in the genome The master thesis of the "Using deep learning to predict gene structures of the coding ge

Ching-Tien Wang 3 Sep 09, 2022
A rough implementation of the paper "A Steering Algorithm for Redirected Walking Using Reinforcement Learning"

A rough implementation of the paper "A Steering Algorithm for Redirected Walking Using Reinforcement Learning"

Somnus `Chen 2 Jun 09, 2022
PyTorch Implementation for AAAI'21 "Do Response Selection Models Really Know What's Next? Utterance Manipulation Strategies for Multi-turn Response Selection"

UMS for Multi-turn Response Selection Implements the model described in the following paper Do Response Selection Models Really Know What's Next? Utte

Taesun Whang 47 Nov 22, 2022
This package is for running the semantic SLAM algorithm using extracted planar surfaces from the received detection

Semantic SLAM This package can perform optimization of pose estimated from VO/VIO methods which tend to drift over time. It uses planar surfaces extra

Hriday Bavle 125 Dec 02, 2022
Asterisk is a framework to generate high-quality training datasets at scale

Asterisk is a framework to generate high-quality training datasets at scale

Mona Nashaat 44 Apr 25, 2022
Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization

Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization This repository contains the source code for the paper (link wi

Rakuten Group, Inc. 0 Nov 19, 2021
CvT2DistilGPT2 is an encoder-to-decoder model that was developed for chest X-ray report generation.

CvT2DistilGPT2 Improving Chest X-Ray Report Generation by Leveraging Warm-Starting This repository houses the implementation of CvT2DistilGPT2 from [1

The Australian e-Health Research Centre 21 Dec 28, 2022
Fake-user-agent-traffic-geneator - Python CLI Tool to generate fake traffic against URLs with configurable user-agents

Fake traffic generator for Gartner Demo Generate fake traffic to URLs with custo

New Relic Experimental 3 Oct 31, 2022
《LXMERT: Learning Cross-Modality Encoder Representations from Transformers》(EMNLP 2020)

The Most Important Thing. Our code is developed based on: LXMERT: Learning Cross-Modality Encoder Representations from Transformers

53 Dec 16, 2022
This repository contains all code and data for the Inside Out Visual Place Recognition task

Inside Out Visual Place Recognition This repository contains code and instructions to reproduce the results for the Inside Out Visual Place Recognitio

15 May 21, 2022
IDA file loader for UF2, created for the DEFCON 29 hardware badge

UF2 Loader for IDA The DEFCON 29 badge uses the UF2 bootloader, which conveniently allows you to dump and flash the firmware over USB as a mass storag

Kevin Colley 6 Feb 08, 2022
Official Pytorch Implementation of GraphiT

GraphiT: Encoding Graph Structure in Transformers This repository implements GraphiT, described in the following paper: Grégoire Mialon*, Dexiong Chen

Inria Thoth 80 Nov 27, 2022
JAXDL: JAX (Flax) Deep Learning Library

JAXDL: JAX (Flax) Deep Learning Library Simple and clean JAX/Flax deep learning algorithm implementations: Soft-Actor-Critic (arXiv:1812.05905) Transf

Patrick Hart 4 Nov 27, 2022
Aspect-Sentiment-Multiple-Opinion Triplet Extraction (NLPCC 2021)

The code and data for the paper "Aspect-Sentiment-Multiple-Opinion Triplet Extraction" Requirements Python 3.6.8 torch==1.2.0 pytorch-transformers==1.

慢半拍 5 Jul 02, 2022
Geometric Sensitivity Decomposition

Geometric Sensitivity Decomposition This repo is the official implementation of A Geometric Perspective towards Neural Calibration via Sensitivity Dec

16 Dec 26, 2022
PyTorch implementation of a Real-ESRGAN model trained on custom dataset

Real-ESRGAN PyTorch implementation of a Real-ESRGAN model trained on custom dataset. This model shows better results on faces compared to the original

Sber AI 160 Jan 04, 2023
GT China coal model

GT China coal model The full version of a China coal transport model with a very high spatial reslution. What it does The code works in a few steps: T

0 Dec 13, 2021
Efficient training of deep recommenders on cloud.

HybridBackend Introduction HybridBackend is a training framework for deep recommenders which bridges the gap between evolving cloud infrastructure and

Alibaba 111 Dec 23, 2022
Official PyTorch Implementation of "AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting".

AgentFormer This repo contains the official implementation of our paper: AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecast

Ye Yuan 161 Dec 23, 2022