3D dataset of humans Manipulating Objects in-the-Wild (MOW)

Zhe Cao

Last update: Nov 6, 2022

Related tags

Deep Learning MOW

Overview

MOW dataset [Website]

This repository maintains our 3D dataset of humans Manipulating Objects in-the-Wild (MOW). The dataset contains 512 images in the wild, spanning 121 object categories with annotation of instance category, 3D object models, 3D hand pose, and object pose annotation.

Setup

(0) Getting Started

Clone this repository, and create local environment with python3.6, and then run: bash setup.sh. Finally, download the MANO model following this repo.

(1) Download the dataset

Download our data (512 examples) from this link.

(2) Visualize the example

python vis_anno.py

Citation

If you find this data useful in your research, please consider citing:

@InProceedings{Cao2021,
  title = {Reconstructing Hand-Object Interactions in the Wild},
  author = {Zhe Cao and Ilija Radosavovic and Angjoo Kanazawa and Jitendra Malik},
  booktitle = {ICCV},
  year = {2021}
}

You might also like...

The code of paper 'Learning to Aggregate and Personalize 3D Face from In-the-Wild Photo Collection'

Learning to Aggregate and Personalize 3D Face from In-the-Wild Photo Collection Pytorch implemetation of paper 'Learning to Aggregate and Personalize

136 Dec 29, 2022

Code release of paper "Deep Multi-View Stereo gone wild"

Deep MVS gone wild Pytorch implementation of "Deep MVS gone wild" (Paper | website) This repository provides the code to reproduce the experiments of

53 Dec 24, 2022

Robust Partial Matching for Person Search in the Wild

APNet for Person Search Introduction This is the code of Robust Partial Matching for Person Search in the Wild accepted in CVPR2020. The Align-to-Part

36 Dec 18, 2022

URIE: Universal Image Enhancementfor Visual Recognition in the Wild

URIE: Universal Image Enhancementfor Visual Recognition in the Wild This is the implementation of the paper "URIE: Universal Image Enhancement for Vis

43 Sep 12, 2022

[CVPR'21] Learning to Recommend Frame for Interactive Video Object Segmentation in the Wild

IVOS-W Paper Learning to Recommend Frame for Interactive Video Object Segmentation in the Wild Zhaoyun Yin, Jia Zheng, Weixin Luo, Shenhan Qian, Hanli

38 Dec 12, 2022

Look Who’s Talking: Active Speaker Detection in the Wild

Look Who's Talking: Active Speaker Detection in the Wild Dependencies pip install -r requirements.txt In addition to the Python dependencies, ffmpeg

60 Dec 8, 2022

Learning High-Speed Flight in the Wild

Learning High-Speed Flight in the Wild This repo contains the code associated to the paper Learning Agile Flight in the Wild. For more information, pl

391 Dec 29, 2022

Code for ICCV2021 paper SPEC: Seeing People in the Wild with an Estimated Camera

SPEC: Seeing People in the Wild with an Estimated Camera [ICCV 2021] SPEC: Seeing People in the Wild with an Estimated Camera, Muhammed Kocabas, Chun-

187 Dec 26, 2022

A python implementation of Yolov5 to detect fire or smoke in the wild in Jetson Xavier nx and Jetson nano

yolov5-fire-smoke-detect-python A python implementation of Yolov5 to detect fire or smoke in the wild in Jetson Xavier nx and Jetson nano You can see

20 Dec 15, 2022

Comments

Code for the Paper

First of all, thank you so much for open sourcing this fantastic dataset. I wanted to use this project to obtain hand-object poses for my own research. Do you plan to release the code for as well?

Thanks

opened by SupreethN 1

Owner

Zhe Cao

PhD in Computer Vision

GitHub

This is an official implementation for the WTW Dataset in "Parsing Table Structures in the Wild " on table detection and table structure recognition.

WTW-Dataset This is an official implementation for the WTW Dataset in "Parsing Table Structures in the Wild " on ICCV 2021. Here, you can download the

109 Dec 29, 2022

Computational inteligence project on faces in the wild dataset

Table of Contents The general idea How these scripts work? Loading data Needed modules and global variables Parsing the arrays in dataset Extracting a

4 Oct 21, 2022

The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining

249 Dec 22, 2022

3D dataset of humans Manipulating Objects in-the-Wild (MOW)

Related tags

Overview

MOW dataset [Website]

Setup

(0) Getting Started

(1) Download the dataset

(2) Visualize the example

Citation

You might also like...

The code of paper 'Learning to Aggregate and Personalize 3D Face from In-the-Wild Photo Collection'

Code release of paper "Deep Multi-View Stereo gone wild"

Robust Partial Matching for Person Search in the Wild

URIE: Universal Image Enhancementfor Visual Recognition in the Wild

[CVPR'21] Learning to Recommend Frame for Interactive Video Object Segmentation in the Wild

Look Who’s Talking: Active Speaker Detection in the Wild

Learning High-Speed Flight in the Wild

Code for ICCV2021 paper SPEC: Seeing People in the Wild with an Estimated Camera

A python implementation of Yolov5 to detect fire or smoke in the wild in Jetson Xavier nx and Jetson nano

Comments

Code for the Paper

Owner

Zhe Cao

This is an official implementation for the WTW Dataset in "Parsing Table Structures in the Wild " on table detection and table structure recognition.

Computational inteligence project on faces in the wild dataset

The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining

Tools for manipulating UVs in the Blender viewport.

MSG-Transformer: Exchanging Local Spatial Information by Manipulating Messenger Tokens

Synthesizing and manipulating 2048x1024 images with conditional GANs

Fader Networks: Manipulating Images by Sliding Attributes - NIPS 2017

Tooling for the Common Objects In 3D dataset.

A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.

Lipstick ain't enough: Beyond Color-Matching for In-the-Wild Makeup Transfer (CVPR 2021)