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Halpe Full-Body Human Keypoints and HOI-Det dataset
What is Halpe?
Halpe is a dataset introduced in AlphaPose paper. It aims at pushing <b>Human Understanding</b> to the extreme. We provide detailed annotation of human keypoints, together with the human-object interaction trplets from HICO-DET. For each person, we annotate 136 keypoints in total, including head,face,body,hand and foot. Below we provide some samples of Halpe dataset.
<div align="center"> <img src="docs/1.jpg", width="400" alt> <img src="docs/2.jpg", width="400" alt> <img src="docs/4.jpg", width="250" alt> <img src="docs/5.jpg", width="250" alt> <img src="docs/3.jpg", width="300" alt> </div>Download
Train annotations [Baidu | Google ]
Val annotations [Baidu | Google ]
Train images from HICO-DET
Val images from COCO
Realtime Demo with tracking
Trained model is available in AlphaPose! Check out its MODEL_ZOO
<div align="center"> <img src="docs/alphapose_136_2.gif", width="400" alt> </div>Keypoints format
We annotate 136 keypoints in total:
//26 body keypoints
{0, "Nose"},
{1, "LEye"},
{2, "REye"},
{3, "LEar"},
{4, "REar"},
{5, "LShoulder"},
{6, "RShoulder"},
{7, "LElbow"},
{8, "RElbow"},
{9, "LWrist"},
{10, "RWrist"},
{11, "LHip"},
{12, "RHip"},
{13, "LKnee"},
{14, "Rknee"},
{15, "LAnkle"},
{16, "RAnkle"},
{17, "Head"},
{18, "Neck"},
{19, "Hip"},
{20, "LBigToe"},
{21, "RBigToe"},
{22, "LSmallToe"},
{23, "RSmallToe"},
{24, "LHeel"},
{25, "RHeel"},
//face
{26-93, 68 Face Keypoints}
//left hand
{94-114, 21 Left Hand Keypoints}
//right hand
{115-135, 21 Right Hand Keypoints}
Illustration:
<div align="center"> <img src="docs/human_model.jpg", width="400" alt><br> 26 body keypoints </div> <div align="center"> <img src="docs/face.jpg", width="400" alt><br> 68 face keypoints </div> <div align="center"> <img src="docs/hand.jpg", width="400" alt><br> 21 hand keypoints </div>Usage
The annotation is in the same format as COCO dataset. For usage, a good start is to check out the vis.py
. We also provide related APIs. See halpecocotools, which can be installed by pip install halpecocotools
.
Evaluation
We adopt the same evaluation metrics as COCO dataset.
Related resources
A concurrent work COCO-WholeBody also annotate the full body keypoints. And HOI-DET for COCO dataset is also available at V-COCO
Citation
If the data helps your research, please cite the following paper:
@article{alphapose,
author = {Fang, Hao-Shu and Li, Jiefeng and Tang, Hongyang and Xu, Chao and Zhu, Haoyi and Xiu, Yuliang and Li, Yong-Lu and Lu, Cewu},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
title = {AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time},
year = {2022}
}