A real-time motion capture system that estimates poses and global translations using only 6 inertial measurement units

Overview

TransPose

Code for our SIGGRAPH 2021 paper "TransPose: Real-time 3D Human Translation and Pose Estimation with Six Inertial Sensors". This repository contains the system implementation, evaluation, and some example IMU data which you can easily run with. Project Page

Live Demo 1Live Demo 2

Usage

Install dependencies

We use python 3.7.6. You should install the newest pytorch chumpy vctoolkit open3d.

Prepare SMPL body model

  1. Download SMPL model from here. You should click SMPL for Python and download the version 1.0.0 for Python 2.7 (10 shape PCs). Then unzip it.
  2. In config.py, set paths.smpl_file to the model path.

Prepare pre-trained network weights

  1. Download weights from here.
  2. In config.py, set paths.weights_file to the weights path.

Prepare test datasets (optional)

  1. Download DIP-IMU dataset from here. We use the raw (unnormalized) data.
  2. Download TotalCapture dataset from here. The ground-truth SMPL poses used in our evaluation are provided by the DIP authors. So you may also need to contact the DIP authors for them.
  3. In config.py, set paths.raw_dipimu_dir to the DIP-IMU dataset path; set paths.raw_totalcapture_dip_dir to the TotalCapture SMPL poses (from DIP authors) path; and set paths.raw_totalcapture_official_dir to the TotalCapture official gt path. Please refer to the comments in the codes for more details.

Run the example

To run the whole system with the provided example IMU measurement sequence, just use:

python example.py

The rendering results in Open3D may be upside down. You can use your mouse to rotate the view.

Run the evaluation

You should preprocess the datasets before evaluation:

python preprocess.py
python evaluate.py

Both offline and online results for DIP-IMU and TotalCapture test datasets will be printed.

Citation

If you find the project helpful, please consider citing us:

@article{TransPoseSIGGRAPH2021,
    author = {Yi, Xinyu and Zhou, Yuxiao and Xu, Feng},
    title = {TransPose: Real-time 3D Human Translation and Pose Estimation with Six Inertial Sensors},
    journal = {ACM Transactions on Graphics}, 
    year = {2021}, 
    month = {08},
    volume = {40},
    number = {4}, 
    articleno = {86},
    publisher = {ACM}
} 
A standard framework for modelling Deep Learning Models for tabular data

PyTorch Tabular aims to make Deep Learning with Tabular data easy and accessible to real-world cases and research alike.

801 Jan 08, 2023
AirPose: Multi-View Fusion Network for Aerial 3D Human Pose and Shape Estimation

AirPose AirPose: Multi-View Fusion Network for Aerial 3D Human Pose and Shape Estimation Check the teaser video This repository contains the code of A

Robot Perception Group 41 Dec 05, 2022
Newt - a Gaussian process library in JAX.

Newt __ \/_ (' \`\ _\, \ \\/ /`\/\ \\ \ \\

AaltoML 0 Nov 02, 2021
Tensorflow Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE

SMU A Tensorflow Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE arXiv https://arxiv.org/abs/211

Fuhang 5 Jan 18, 2022
Erpnext app for make employee salary on payroll entry based on one or more project with percentage for all project equal 100 %

Project Payroll this app for make payroll for employee based on projects like project on 30 % and project 2 70 % as account dimension it makes genral

Ibrahim Morghim 8 Jan 02, 2023
Spatial Action Maps for Mobile Manipulation (RSS 2020)

spatial-action-maps Update: Please see our new spatial-intention-maps repository, which extends this work to multi-agent settings. It contains many ne

Jimmy Wu 27 Nov 30, 2022
Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning

Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning. Circuit Training is an open-s

Google Research 479 Dec 25, 2022
Implementation of the "PSTNet: Point Spatio-Temporal Convolution on Point Cloud Sequences" paper.

PSTNet: Point Spatio-Temporal Convolution on Point Cloud Sequences Introduction Point cloud sequences are irregular and unordered in the spatial dimen

Hehe Fan 63 Dec 09, 2022
Small utility to demangle Nim symbols in callgrind files

nim_callgrind A small utility to demangle Nim symbols from callgrind files. Usage Run your (Nim) program with something like this: valgrind --tool=cal

kraptor 3 Feb 15, 2022
Advances in Neural Information Processing Systems (NeurIPS), 2020.

What is being transferred in transfer learning? This repo contains the code for the following paper: Behnam Neyshabur*, Hanie Sedghi*, Chiyuan Zhang*.

Google Research 36 Aug 26, 2022
A curated list of awesome projects and resources related fastai

A curated list of awesome projects and resources related fastai

Tanishq Abraham 138 Dec 22, 2022
Tooling for GANs in TensorFlow

TensorFlow-GAN (TF-GAN) TF-GAN is a lightweight library for training and evaluating Generative Adversarial Networks (GANs). Can be installed with pip

803 Dec 24, 2022
Image based Human Fall Detection

Here I integrated the YOLOv5 object detection algorithm with my own created dataset which consists of human activity images to achieve low cost, high accuracy, and real-time computing requirements

UTTEJ KUMAR 12 Dec 11, 2022
A curated list of programmatic weak supervision papers and resources

A curated list of programmatic weak supervision papers and resources

Jieyu Zhang 118 Jan 02, 2023
AfriBERTa: Exploring the Viability of Pretrained Multilingual Language Models for Low-resourced Languages

AfriBERTa: Exploring the Viability of Pretrained Multilingual Language Models for Low-resourced Languages This repository contains the code for the pa

Kelechi 40 Nov 24, 2022
最新版本yolov5+deepsort目标检测和追踪,支持5.0版本可训练自己数据集

使用YOLOv5+Deepsort实现车辆行人追踪和计数,代码封装成一个Detector类,更容易嵌入到自己的项目中。

422 Dec 30, 2022
A simple baseline for the 2022 IEEE GRSS Data Fusion Contest (DFC2022)

DFC2022 Baseline A simple baseline for the 2022 IEEE GRSS Data Fusion Contest (DFC2022) This repository uses TorchGeo, PyTorch Lightning, and Segmenta

isaac 24 Nov 28, 2022
CPU inference engine that delivers unprecedented performance for sparse models

The DeepSparse Engine is a CPU runtime that delivers unprecedented performance by taking advantage of natural sparsity within neural networks to reduce compute required as well as accelerate memory b

Neural Magic 1.2k Jan 09, 2023
CoCosNet v2: Full-Resolution Correspondence Learning for Image Translation

CoCosNet v2: Full-Resolution Correspondence Learning for Image Translation (CVPR 2021, oral presentation) CoCosNet v2: Full-Resolution Correspondence

Microsoft 308 Dec 07, 2022
PyTorch code accompanying our paper on Maximum Entropy Generators for Energy-Based Models

Maximum Entropy Generators for Energy-Based Models All experiments have tensorboard visualizations for samples / density / train curves etc. To run th

Rithesh Kumar 135 Oct 27, 2022