Data
Meta_Album_ACT_40_Extended

Meta_Album_ACT_40_Extended

active ARFF CC BY-NC 4.0 Visibility: public Uploaded 08-11-2022 by Meta Album
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## Meta-Album Stanford 40 Actions Dataset (Extended) * The Stanford 40 Actions dataset(http://vision.stanford.edu/Datasets/40actions.html) contains images of humans performing 40 actions. There are 9 532 images in total with 180-300 images per action class. The dataset is designed for understanding human actions in still images. For Meta-Album, the dataset is preprocessed and images are resized into 128x128 pixels using Open-CV. ### Dataset Details ![](https://meta-album.github.io/assets/img/samples/ACT_40.png) Meta Album ID: HUM_ACT.ACT_40 Meta Album URL: [https://meta-album.github.io/datasets/ACT_40.html](https://meta-album.github.io/datasets/ACT_40.html) Domain ID: HUM_ACT Domain Name: Human Actions Dataset ID: ACT_40 Dataset Name: Stanford 40 Actions Short Description: Stanford 40 Actions dataset with images of humans performing 40 actions. \# Classes: 40 \# Images: 3389 Keywords: human actions Data Format: images Image size: 128x128 License (original data release): Cite paper to use dataset License (Meta-Album data release): CC BY-NC 4.0 License URL (Meta-Album data release): [https://creativecommons.org/licenses/by-nc/4.0/](https://creativecommons.org/licenses/by-nc/4.0/) Source: Stanford 40 Actions Source URL: http://vision.stanford.edu/Datasets/40actions.html Original Author: B. Yao, X. Jiang, A. Khosla, A.L. Lin, L.J. Guibas, and L. Fei-Fei. Original contact: bangpeng@cs.stanford.edu Meta Album author: Jilin He Created Date: 01 March 2022 Contact Name: Ihsan Ullah Contact Email: meta-album@chalearn.org Contact URL: [https://meta-album.github.io/](https://meta-album.github.io/) ### Cite this dataset ``` @INPROCEEDINGS{6126386, author={Yao, Bangpeng and Jiang, Xiaoye and Khosla, Aditya and Lin, Andy Lai and Guibas, Leonidas and Fei-Fei, Li}, booktitle={2011 International Conference on Computer Vision}, title={Human action recognition by learning bases of action attributes and parts}, year={2011}, pages={1331-1338}, doi={10.1109/ICCV.2011.6126386} } ``` ### 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 = {https://meta-album.github.io/}, year = {2022} } ``` ### More For more information on the Meta-Album dataset, please see the [[NeurIPS 2022 paper]](https://meta-album.github.io/paper/Meta-Album.pdf) For details on the dataset preprocessing, please see the [[supplementary materials]](https://openreview.net/attachment?id=70_Wx-dON3q&name=supplementary_material) Supporting code can be found on our [[GitHub repo]](https://github.com/ihsaan-ullah/meta-album) Meta-Album on Papers with Code [[Meta-Album]](https://paperswithcode.com/dataset/meta-album) ### Other versions of this dataset [[Micro]](https://www.openml.org/d/44247) [[Mini]](https://www.openml.org/d/44291)

3 features

CATEGORY (target)string40 unique values
0 missing
FILE_NAMEstring3389 unique values
0 missing
SUPER_CATEGORYnumeric0 unique values
3389 missing

19 properties

3389
Number of instances (rows) of the dataset.
3
Number of attributes (columns) of the dataset.
40
Number of distinct values of the target attribute (if it is nominal).
3389
Number of missing values in the dataset.
3389
Number of instances with at least one value missing.
1
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
100
Percentage of instances having missing values.
33.33
Percentage of missing values.
1
Average class difference between consecutive instances.
33.33
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
3.25
Percentage of instances belonging to the most frequent class.
110
Number of instances belonging to the most frequent class.
0.32
Percentage of instances belonging to the least frequent class.
11
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

1 tasks

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