Motion and Shape Capture from Sparse Markers

Related tags

Deep Learningmoshpp
Overview

MoSh++

This repository contains the official chumpy implementation of mocap body solver used for AMASS:

AMASS: Archive of Motion Capture as Surface Shapes
Naureen Mahmood, Nima Ghorbani, Nikolaus F. Troje, Gerard Pons-Moll, Michael J. Black
Full paper | Video | Project website | Poster

Description

This repository holds the code for MoSh++, introduced in AMASS, ICCV'19. MoSh++ is the upgraded version of MoSh, Sig.Asia'2014. Given a labeled marker-based motion capture (mocap) c3d file and the correspondences of the marker labels to the locations on the body, MoSh can return model parameters for every frame of the mocap sequence. The current MoSh++ code works with the following models:

Installation

The Current repository requires Python 3.7 and chumpy; a CPU based auto-differentiation package. This package is assumed to be used along with SOMA, the mocap auto-labeling package. Please install MoSh++ inside the conda environment of SOMA. Clone the moshpp repository, and run the following from the root directory:

sudo apt install libeigen3-dev
sudo apt install libtbb-dev

pip install -r requirements.txt

cd src/moshpp/scan2mesh/mesh_distance
make

cd ../../../..
python setup.py install

Tutorials

This repository is a complementary package to SOMA, an automatic mocap solver. Please refer to the SOMA repository for tutorials and use cases.

Citation

Please cite the following paper if you use this code directly or indirectly in your research/projects:

@inproceedings{AMASS:2019,
  title={AMASS: Archive of Motion Capture as Surface Shapes},
  author={Mahmood, Naureen and Ghorbani, Nima and Troje, Nikolaus F. and Pons-Moll, Gerard and Black, Michael J.},
  booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
  year={2019},
  month = {Oct},
  url = {https://amass.is.tue.mpg.de},
  month_numeric = {10}
}

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 MoSh++ data and software, (the "Data & Software"), software, scripts, and animations. By downloading and/or using the Data & Software (including downloading, cloning, installing, and any other use of this 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 Data & Software. Any infringement of the terms of this agreement will automatically terminate your rights under this License.

The software is compiled using CGAL sources following the license in CGAL_LICENSE.pdf

Contact

The code in this repository is developed by Nima Ghorbani while at Max-Planck Institute for Intelligent Systems, Tübingen, Germany.

If you have any questions you can contact us at [email protected].

For commercial licensing, contact [email protected]

Owner
Nima Ghorbani
Research Engineer at Max-Planck Institute for Intelligent Systems. In love with math and its applications in perceiving systems.
Nima Ghorbani
Repository containing detailed experiments related to the paper "Memotion Analysis through the Lens of Joint Embedding".

Memotion Analysis Through The Lens Of Joint Embedding This repository contains the experiments conducted as described in the paper 'Memotion Analysis

Nethra Gunti 1 Mar 16, 2022
Robot Reinforcement Learning on the Constraint Manifold

Implementation of "Robot Reinforcement Learning on the Constraint Manifold"

31 Dec 05, 2022
Model Zoo of BDD100K Dataset

Model Zoo of BDD100K Dataset

ETH VIS Group 200 Dec 27, 2022
a curated list of docker-compose files prepared for testing data engineering tools, databases and open source libraries.

data-services A repository for storing various Data Engineering docker-compose files in one place. How to use it ? Set the required settings in .env f

BigData.IR 525 Dec 03, 2022
salabim - discrete event simulation in Python

Object oriented discrete event simulation and animation in Python. Includes process control features, resources, queues, monitors. statistical distrib

181 Dec 21, 2022
Official Implementation of "DialogLM: Pre-trained Model for Long Dialogue Understanding and Summarization."

DialogLM Code for AAAI 2022 paper: DialogLM: Pre-trained Model for Long Dialogue Understanding and Summarization. Pre-trained Models We release two ve

Microsoft 92 Dec 19, 2022
HybVIO visual-inertial odometry and SLAM system

HybVIO A visual-inertial odometry system with an optional SLAM module. This is a research-oriented codebase, which has been published for the purposes

Spectacular AI 320 Jan 03, 2023
Jaxtorch (a jax nn library)

Jaxtorch (a jax nn library) This is my jax based nn library. I created this because I was annoyed by the complexity and 'magic'-ness of the popular ja

nshepperd 17 Dec 08, 2022
Machine Learning Platform for Kubernetes

Reproduce, Automate, Scale your data science. Welcome to Polyaxon, a platform for building, training, and monitoring large scale deep learning applica

polyaxon 3.2k Dec 23, 2022
Combining Diverse Feature Priors

Combining Diverse Feature Priors This repository contains code for reproducing the results of our paper. Paper: https://arxiv.org/abs/2110.08220 Blog

Madry Lab 5 Nov 12, 2022
The code written during my Bachelor Thesis "Classification of Human Whole-Body Motion using Hidden Markov Models".

This code was written during the course of my Bachelor thesis Classification of Human Whole-Body Motion using Hidden Markov Models. Some things might

Matthias Plappert 14 Dec 06, 2022
The Official Repository for "Generalized OOD Detection: A Survey"

Generalized Out-of-Distribution Detection: A Survey 1. Overview This repository is with our survey paper: Title: Generalized Out-of-Distribution Detec

Jingkang Yang 338 Jan 03, 2023
PyTorch implementation of normalizing flow models

PyTorch implementation of normalizing flow models

Vincent Stimper 242 Jan 02, 2023
Solve a Rubiks Cube using Python Opencv and Kociemba module

Rubiks_Cube_Solver Solve a Rubiks Cube using Python Opencv and Kociemba module Main Steps Get the countours of the cube check whether there are tota

Adarsh Badagala 176 Jan 01, 2023
Official Pytorch Implementation of Unsupervised Image Denoising with Frequency Domain Knowledge

Unsupervised Image Denoising with Frequency Domain Knowledge (BMVC 2021 Oral) : Official Project Page This repository provides the official PyTorch im

Donggon Jang 12 Sep 26, 2022
Detectron2 for Document Layout Analysis

Detectron2 trained on PubLayNet dataset This repo contains the training configurations, code and trained models trained on PubLayNet dataset using Det

Himanshu 163 Nov 21, 2022
PyTorch Live is an easy to use library of tools for creating on-device ML demos on Android and iOS.

PyTorch Live is an easy to use library of tools for creating on-device ML demos on Android and iOS. With Live, you can build a working mobile app ML demo in minutes.

559 Jan 01, 2023
Analysis of Smiles through reservoir sampling & RDkit

Analysis of Smiles through reservoir sampling and machine learning (under development). This is a simple project that includes two Jupyter files for t

Aurimas A. Nausėdas 6 Aug 30, 2022
Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph, ICSE 2022

PyCRE Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph, ICSE 2022 Dependencies This project is developed

<a href=[email protected]"> 7 May 06, 2022
PyTorch implementation for "Mining Latent Structures with Contrastive Modality Fusion for Multimedia Recommendation"

MIRCO PyTorch implementation for paper: Latent Structures Mining with Contrastive Modality Fusion for Multimedia Recommendation Dependencies Python 3.

Big Data and Multi-modal Computing Group, CRIPAC 9 Dec 08, 2022