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## Meta-Album MPII Human Pose Dataset Dataset (Extended) * The MPII Human Pose dataset ( is a state of the art benchmark for evaluation of articulated human pose estimation. It includes around 25 000 images containing over 40 000 people with annotated body joints. The images were systematically collected using an established taxonomy of every day human activities. Overall the dataset covers 410 human activities and each image is provided with an activity label. Each image was extracted from a YouTube video. Like other Meta-Album datasets, this dataset is preprocessed and all images are resized into 128x128 pixels. ### Dataset Details ![]( Meta Album ID: HUM_ACT.ACT_410 Meta Album URL: []( Domain ID: HUM_ACT Domain Name: Human Actions Dataset ID: ACT_410 Dataset Name: MPII Human Pose Dataset Short Description: MPII Human Pose Dataset with images of humans performing 410 activities. \# Classes: 29 \# Images: 2402 Keywords: human actions, sports Data Format: images Image size: 128x128 License (original data release): Simplified BSD License License URL(original data release): License (Meta-Album data release): Simplified BSD License License URL (Meta-Album data release): []( Source: MPII Human Pose Dataset Source URL: Original Author: Mykhaylo Andriluka and Leonid Pishchulin and Peter Gehler and Schiele, Bernt Original contact: Meta Album author: Jilin He Created Date: 01 March 2022 Contact Name: Ihsan Ullah Contact Email: Contact URL: []( ### Cite this dataset ``` @INPROCEEDINGS{6909866, author={Andriluka, Mykhaylo and Pishchulin, Leonid and Gehler, Peter and Schiele, Bernt}, booktitle={2014 IEEE Conference on Computer Vision and Pattern Recognition}, title={2D Human Pose Estimation: New Benchmark and State of the Art Analysis}, year={2014}, pages={3686-3693}, doi={10.1109/CVPR.2014.471} } ``` ### Cite Meta-Album ``` @inproceedings{meta-album-2022, title={Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification}, author={Ullah, Ihsan and Carrion, Dustin and Escalera, Sergio and Guyon, Isabelle M and Huisman, Mike and Mohr, Felix and van Rijn, Jan N and Sun, Haozhe and Vanschoren, Joaquin and Vu, Phan Anh}, booktitle={Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track}, url = {}, year = {2022} } ``` ### More For more information on the Meta-Album dataset, please see the [[NeurIPS 2022 paper]]( For details on the dataset preprocessing, please see the [[supplementary materials]]( Supporting code can be found on our [[GitHub repo]]( Meta-Album on Papers with Code [[Meta-Album]]( ### Other versions of this dataset [[Micro]]( [[Mini]](

3 features

CATEGORY (target)string29 unique values
0 missing
FILE_NAMEstring2402 unique values
0 missing
SUPER_CATEGORYnumeric0 unique values
2402 missing

19 properties

Number of instances (rows) of the dataset.
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
Number of missing values in the dataset.
Number of instances with at least one value missing.
Number of numeric attributes.
Number of nominal attributes.
Percentage of binary attributes.
Percentage of instances having missing values.
Average class difference between consecutive instances.
Percentage of missing values.
Number of attributes divided by the number of instances.
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
Number of binary attributes.

1 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: CATEGORY
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