Human4D Dataset tools for processing and visualization

Overview

HUMAN4D: A Human-Centric Multimodal Dataset for Motions & Immersive Media

HUMAN4D constitutes a large and multimodal 4D dataset that contains a variety of human activities simultaneously captured by a professional marker-based MoCap, a volumetric capture and an audio recording system.

The related paper can be found here in PDF.

You can download the dataset from Zenodo (in various parts):

For data that are not publicly available but are included in the HUMAN4D dataset, contact us @ tofis3d [at] central.ntua.gr.

alt text Pictures taken during the preparation and capturing of the HUMAN4D dataset. The room was equipped with 24 Vicon MXT40S cameras rigidly placed on the walls, while a portable volumetric capturing system (https://github.com/VCL3D/VolumetricCapture) with 4 Intel RealSense D415 depth sensors was temporarily set up to capture the RGBD data cues.

alt text HW-SYNCed multi-view RGBD samples (4 RGBD frames each) from "stretching_n_talking"(top) and "basket-ball_dribbling"(bottom) activities.

alt text 3D Scanning using a custom photogrammetry rig with 96 cameras, photos were taken of the actor (left) and reconstructed into a 3D textured mesh using Agisoft Metashape (right).

alt text Reconstructed mesh-based volumetric data with (Left) color per vertex visualization in 3 voxel-grid resolutions, i.e. r= 5, r= 6 andr= 7 and (Right) textured 3D mesh sample in voxel-grid resolution for r= 6.

alt text Merged reconstructed point-cloud from one single mRGBD frame from various views.

If you used the dataset or found this work useful, please cite:

@article{chatzitofis2020human4d,
  title={HUMAN4D: A Human-Centric Multimodal Dataset for Motions and Immersive Media},
  author={Chatzitofis, Anargyros and Saroglou, Leonidas and Boutis, Prodromos and Drakoulis, Petros and Zioulis, Nikolaos and Subramanyam, Shishir and Kevelham, Bart and Charbonnier, Caecilia and Cesar, Pablo and Zarpalas, Dimitrios and others},
  journal={IEEE Access},
  volume={8},
  pages={176241--176262},
  year={2020},
  publisher={IEEE}
}
Owner
tofis
tofis
Hough Transform and Hough Line Transform Using OpenCV

Hough transform is a feature extraction method for detecting simple shapes such as circles, lines, etc in an image. Hough Transform and Hough Line Transform is implemented in OpenCV with two methods;

Happy N. Monday 3 Feb 15, 2022
Kaggleship: Kaggle Notebooks

Kaggleship: Kaggle Notebooks This repository contains my Kaggle notebooks. They are generally about data science, machine learning, and deep learning.

Erfan Sobhaei 1 Jan 25, 2022
3D dataset of humans Manipulating Objects in-the-Wild (MOW)

MOW dataset [Website] This repository maintains our 3D dataset of humans Manipulating Objects in-the-Wild (MOW). The dataset contains 512 images in th

Zhe Cao 28 Nov 06, 2022
🐦 Opytimizer is a Python library consisting of meta-heuristic optimization techniques.

Opytimizer: A Nature-Inspired Python Optimizer Welcome to Opytimizer. Did you ever reach a bottleneck in your computational experiments? Are you tired

Gustavo Rosa 546 Dec 31, 2022
Lightweight Salient Object Detection in Optical Remote Sensing Images via Feature Correlation

CorrNet This project provides the code and results for 'Lightweight Salient Object Detection in Optical Remote Sensing Images via Feature Correlation'

Gongyang Li 13 Nov 03, 2022
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition

AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition [ArXiv] [Project Page] This repository is the official implementation of AdaMML:

International Business Machines 43 Dec 26, 2022
Scientific Computation Methods in C and Python (Open for Hacktoberfest 2021)

Sci - cpy README is a stub. Do expand it. Objective This repository is meant to be a ready reference for scientific computation methods. Do ⭐ it if yo

Sandip Dutta 7 Oct 12, 2022
Code for the TIP 2021 Paper "Salient Object Detection with Purificatory Mechanism and Structural Similarity Loss"

PurNet Project for the TIP 2021 Paper "Salient Object Detection with Purificatory Mechanism and Structural Similarity Loss" Abstract Image-based salie

Jinming Su 4 Aug 25, 2022
Quantum-enhanced transformer neural network

Example of a Quantum-enhanced transformer neural network Get the code: git clone https://github.com/rdisipio/qtransformer.git cd qtransformer Create

Riccardo Di Sipio 61 Nov 08, 2022
This repository contains the code and models for the following paper.

DC-ShadowNet Introduction This is an implementation of the following paper DC-ShadowNet: Single-Image Hard and Soft Shadow Removal Using Unsupervised

AuAgCu 65 Dec 27, 2022
PyTorch implementation of popular datasets and models in remote sensing

PyTorch Remote Sensing (torchrs) (WIP) PyTorch implementation of popular datasets and models in remote sensing tasks (Change Detection, Image Super Re

isaac 222 Dec 28, 2022
Hardware accelerated, batchable and differentiable optimizers in JAX.

JAXopt Installation | Examples | References Hardware accelerated (GPU/TPU), batchable and differentiable optimizers in JAX. Installation JAXopt can be

Google 621 Jan 08, 2023
Pyramid Scene Parsing Network, CVPR2017.

Pyramid Scene Parsing Network by Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia, details are in project page. Introduction This

Hengshuang Zhao 1.5k Jan 05, 2023
GMFlow: Learning Optical Flow via Global Matching

GMFlow GMFlow: Learning Optical Flow via Global Matching Authors: Haofei Xu, Jing Zhang, Jianfei Cai, Hamid Rezatofighi, Dacheng Tao We streamline the

Haofei Xu 298 Jan 04, 2023
Gauge equivariant mesh cnn

Geometric Mesh CNN The code in this repository is an implementation of the Gauge Equivariant Mesh CNN introduced in the paper Gauge Equivariant Mesh C

50 Dec 18, 2022
Official PyTorch implementation of the ICRA 2021 paper: Adversarial Differentiable Data Augmentation for Autonomous Systems.

Adversarial Differentiable Data Augmentation This repository provides the official PyTorch implementation of the ICRA 2021 paper: Adversarial Differen

Manli 3 Oct 15, 2022
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)

PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J

AI Wizards for Software Management (AWSM) Research Group 14 Nov 13, 2022
PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Condition Layer Normalization and Semi-Supervised Training in Text-To-Speech

Cross-Speaker-Emotion-Transfer - PyTorch Implementation PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Conditio

Keon Lee 114 Jan 08, 2023
InsightFace: 2D and 3D Face Analysis Project on MXNet and PyTorch

InsightFace: 2D and 3D Face Analysis Project on MXNet and PyTorch

Deep Insight 13.2k Jan 06, 2023