From a body shape, infer the anatomic skeleton.

Related tags

Deep LearningOSSO
Overview

OSSO: Obtaining Skeletal Shape from Outside (CVPR 2022)

This repository contains the official implementation of the skeleton inference from:

OSSO: Obtaining Skeletal Shape from Outside
Marilyn Keller, Silvia Zuffi, Michael J. Black and Sergi Pujades
Full paper | Project website

Given a body shape with SMPL or STAR topology (in blue), we infer the underlying skeleton (in yellow). teaser

Installation

Please follow the installation instruction in installation.md to setup all the required packages and models.

Run skeleton inference

The skeleton can be inferred either from a SMPL or STAR mesh.

python main.py  --mesh_input data/demo/body_female.ply --gender female -D -v

The final infered skeleton will be saved in the out folder and the intermediate meshes in out/tmp.

Citation

If you find this model & software useful in your research, please consider citing:

@inproceedings{Keller:CVPR:2022,
  title = {{OSSO}: Obtaining Skeletal Shape from Outside},
  author = {Keller, Marilyn and Zuffi, Silvia and Black, Michael J. and Pujades, Sergi},
  booktitle = {Proceedings IEEE/CVF Conf.~on Computer Vision and Pattern Recognition (CVPR)},
  month = jun,
  year = {2022},
  month_numeric = {6}}

Acknowledgements

OSSO uses the Stitched Puppet by Silvia Zuffi and Michael J. Black, and the body model STAR by Ahmed Osman et al. The model was applied on AGORA (Priyanka Patel et al.) for demonstration.

This research has been conducted using the UK Biobank Resource under the Approved Project ID 51951. The authors thank the International Max Planck Research School for Intelligent Systems for supporting Marilyn Keller. Sergi Pujades’ work was funded by the ANR SEMBA project. We thank Anatoscope (www.anatoscope.com) for the initial skeleton mesh and useful discussions.

We also thank A. A. Osman for his helpful advice on body models, P. Patel for helping test OSSO on AGORA, T. McConnel, Y. Xiu, S. Tripathi and T. Yin for helping with the submission and release, and P. Ghosh, J. Tesch, A. Chandrasekaran, V. F. Abrevaya, S. Sanyal, O. Ben-Dov and P. Forte for fruitful discussions, advice and proofreading.

License

This code and model are available for non-commercial scientific research purposes as defined in the LICENSE.txt file.

Contact

For more questions, please contact [email protected]

For commercial licensing, please contact [email protected]

Owner
Marilyn Keller
I am currently a 3rd-Year CS Ph.D. student, working at Max Planck Institute for Intelligent Systems.
Marilyn Keller
A Comparative Framework for Multimodal Recommender Systems

Cornac Cornac is a comparative framework for multimodal recommender systems. It focuses on making it convenient to work with models leveraging auxilia

Preferred.AI 671 Jan 03, 2023
UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning

UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning This is the official PyTorch implementation for UniMoCo pape

dddzg 49 Jan 02, 2023
Large dataset storage format for Pytorch

H5Record Large dataset ( 100G, = 1T) storage format for Pytorch (wip) Support python 3 pip install h5record Why? Writing large dataset is still a

theblackcat102 43 Oct 22, 2022
Proof of concept GnuCash Webinterface

Proof of Concept GnuCash Webinterface This may one day be a something truly great. Milestones [ ] Browse accounts and view transactions [ ] Record sim

Josh 14 Dec 28, 2022
Official code for our CVPR '22 paper "Dataset Distillation by Matching Training Trajectories"

Dataset Distillation by Matching Training Trajectories Project Page | Paper This repo contains code for training expert trajectories and distilling sy

George Cazenavette 256 Jan 05, 2023
Hierarchical Memory Matching Network for Video Object Segmentation (ICCV 2021)

Hierarchical Memory Matching Network for Video Object Segmentation Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim

Hongje Seong 72 Dec 14, 2022
Attendance Monitoring with Face Recognition using Python

Attendance Monitoring with Face Recognition using Python A python GUI integrated attendance system using face recognition to take attendance. In this

Vaibhav Rajput 2 Jun 21, 2022
Implementation of SiameseXML (ICML 2021)

SiameseXML Code for SiameseXML: Siamese networks meet extreme classifiers with 100M labels Best Practices for features creation Adding sub-words on to

Extreme Classification 35 Nov 06, 2022
The official repository for "Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning" paper.

Intermdiate layer matters - SSL The official repository for "Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning" paper. Downl

Aakash Kaku 35 Sep 19, 2022
A PyTorch implementation of EventProp [https://arxiv.org/abs/2009.08378], a method to train Spiking Neural Networks

Spiking Neural Network training with EventProp This is an unofficial PyTorch implemenation of EventProp, a method to compute exact gradients for Spiki

Pedro Savarese 35 Jul 29, 2022
An implementation for `Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction`

Text2Event An implementation for Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction Please contact Yaojie Lu (@

Roger 153 Jan 07, 2023
SOFT: Softmax-free Transformer with Linear Complexity, NeurIPS 2021 Spotlight

SOFT: Softmax-free Transformer with Linear Complexity SOFT: Softmax-free Transformer with Linear Complexity, Jiachen Lu, Jinghan Yao, Junge Zhang, Xia

Fudan Zhang Vision Group 272 Dec 25, 2022
NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.

NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.

100 Sep 28, 2022
[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs

Context Encoders: Feature Learning by Inpainting CVPR 2016 [Project Website] [Imagenet Results] Sample results on held-out images: This is the trainin

Deepak Pathak 829 Dec 31, 2022
PyTorch implementation of Value Iteration Networks (VIN): Clean, Simple and Modular. Visualization in Visdom.

VIN: Value Iteration Networks This is an implementation of Value Iteration Networks (VIN) in PyTorch to reproduce the results.(TensorFlow version) Key

Xingdong Zuo 215 Dec 07, 2022
3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans.

3DMV 3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans. This work is based on our ECCV'18 p

Владислав Молодцов 0 Feb 06, 2022
Gesture Volume Control Using OpenCV and MediaPipe

This Project Uses OpenCV and MediaPipe Hand solutions to identify hands and Change system volume by taking thumb and index finger positions

Pratham Bhatnagar 6 Sep 12, 2022
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility

Tensorpack is a neural network training interface based on TensorFlow. Features: It's Yet Another TF high-level API, with speed, and flexibility built

Tensorpack 6.2k Jan 09, 2023
YOLOv4-v3 Training Automation API for Linux

This repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset or label your dataset using our

BMW TechOffice MUNICH 626 Dec 31, 2022
Modular Probabilistic Programming on MXNet

MXFusion | | | | Tutorials | Documentation | Contribution Guide MXFusion is a modular deep probabilistic programming library. With MXFusion Modules yo

Amazon 100 Dec 10, 2022