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CelebFaces Attributes (CelebA) Dataset
2D Classification
Aesthetics
|...
许可协议: CC-BY-SA 4.0

Overview

Context

A popular component of computer vision and deep learning revolves around identifying faces for various applications from logging into your phone with your face or searching through surveillance images for a particular suspect. This dataset is great for training and testing models for face detection, particularly for recognising facial attributes such as finding people with brown hair, are smiling, or wearing glasses. Images cover large pose variations, background clutter, diverse people, supported by a large quantity of images and rich annotations. This data was originally collected by researchers at MMLAB, The Chinese University of Hong Kong (specific reference in Acknowledgment section).

Content

Overall

  • 202,599 number of face images of various celebrities
  • 10,177 unique identities, but names of identities are not given
  • 40 binary attribute annotations per image
  • 5 landmark locations

Data Files

  • img_align_celeba.zip: All the face images, cropped and aligned
  • list_eval_partition.csv: Recommended partitioning of images into training, validation, testing sets. Images 1-162770 are training, 162771-182637 are validation, 182638-202599 are testing
  • list_bbox_celeba.csv: Bounding box information for each image. "x_1" and "y_1" represent the upper left point coordinate of bounding box. "width" and "height" represent the width and height of bounding box
  • list_landmarks_align_celeba.csv: Image landmarks and their respective coordinates. There are 5 landmarks: left eye, right eye, nose, left mouth, right mouth
  • list_attr_celeba.csv: Attribute labels for each image. There are 40 attributes. "1" represents positive while "-1" represents negative

Acknowledgements

Original data and banner image source came from http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
As mentioned on the website, the CelebA dataset is available for non-commercial research purposes only. For specifics please refer to the website.

The creators of this dataset wrote the following paper employing CelebA for face detection:

S. Yang, P. Luo, C. C. Loy, and X. Tang, "From Facial Parts Responses to Face Detection: A Deep Learning Approach", in IEEE International Conference on Computer Vision (ICCV), 2015

Inspiration

  • Can you train a model that can detect particular facial attributes?
  • Which images contain people that are smiling?
  • Does someone have straight or wavy hair?
数据概要
数据格式
image,
数据量
202.603K
文件大小
1361.61GB
发布方
Jessica Li
| 数据量 202.603K | 大小 1361.61GB
CelebFaces Attributes (CelebA) Dataset
2D Classification
Aesthetics
许可协议: CC-BY-SA 4.0

Overview

Context

A popular component of computer vision and deep learning revolves around identifying faces for various applications from logging into your phone with your face or searching through surveillance images for a particular suspect. This dataset is great for training and testing models for face detection, particularly for recognising facial attributes such as finding people with brown hair, are smiling, or wearing glasses. Images cover large pose variations, background clutter, diverse people, supported by a large quantity of images and rich annotations. This data was originally collected by researchers at MMLAB, The Chinese University of Hong Kong (specific reference in Acknowledgment section).

Content

Overall

  • 202,599 number of face images of various celebrities
  • 10,177 unique identities, but names of identities are not given
  • 40 binary attribute annotations per image
  • 5 landmark locations

Data Files

  • img_align_celeba.zip: All the face images, cropped and aligned
  • list_eval_partition.csv: Recommended partitioning of images into training, validation, testing sets. Images 1-162770 are training, 162771-182637 are validation, 182638-202599 are testing
  • list_bbox_celeba.csv: Bounding box information for each image. "x_1" and "y_1" represent the upper left point coordinate of bounding box. "width" and "height" represent the width and height of bounding box
  • list_landmarks_align_celeba.csv: Image landmarks and their respective coordinates. There are 5 landmarks: left eye, right eye, nose, left mouth, right mouth
  • list_attr_celeba.csv: Attribute labels for each image. There are 40 attributes. "1" represents positive while "-1" represents negative

Acknowledgements

Original data and banner image source came from http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
As mentioned on the website, the CelebA dataset is available for non-commercial research purposes only. For specifics please refer to the website.

The creators of this dataset wrote the following paper employing CelebA for face detection:

S. Yang, P. Luo, C. C. Loy, and X. Tang, "From Facial Parts Responses to Face Detection: A Deep Learning Approach", in IEEE International Conference on Computer Vision (ICCV), 2015

Inspiration

  • Can you train a model that can detect particular facial attributes?
  • Which images contain people that are smiling?
  • Does someone have straight or wavy hair?
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