bodym.yaml

Name: BodyM Dataset
Description: |
  The first large public body measurement dataset including 8978 frontal and lateral
  silhouettes for 2505 real subjects, paired with height, weight and 14 body
  measurements. The following artifacts are made available for each subject.
    - Subject Height
    - Subject Weight
    - Subject Gender
    - Two black-and-white silhouette images of subject standing in frontal and side pose
    respectively with full body in view.
    - 14 body measurements in cm - {ankle girth, arm-length, bicep girth, calf girth,
                                  chest girth, forearm girth, height, hip girth, leg-length,
                                  shoulder-breadth, shoulder-to-crotch length, thigh girth,
                                  waist girth, wrist girth}
  
  The data is split into 3 sets - Training, Test Set A, Test Set B. For the training and
  Test-A sets, subjects are photographed and 3D-scanned by in a lab by technicians. For
  the Test-B set, subjects are scanned in the lab, but photographed in a less-controlled
  environment with diverse camera orientations and lighting conditions, to simulate
  in-the-wild image capture. Some subjects have been photographed more than once with
  different clothing in order to test robustness of the dataset.
Documentation: https://adversarialbodysim.github.io/
Contact: Post any questions to [re:Post](https://repost.aws/tags/questions/TApd0Wl5P8S9O6riTWmh-cGw/aws-open-data) and use the `AWS Open Data` tag.
ManagedBy: Amazon
UpdateFrequency: None
Tags:
  - amazon.science
  - computer vision
  - deep learning
License: Creative Commons Attribution-Non Commercial 4.0 International Public License - https://creativecommons.org/licenses/by/4.0/legalcode
Resources:
  - Description: This S3 bucket has height, weight, gender, measurements and two silhouette images for each type of data
    ARN: arn:aws:s3:::amazon-bodym
    Region: us-west-2
    Type: S3 Bucket
DataAtWork:
  Publications:
    - Title: Human Body Measurement Estimation with Adversarial Augmentation
      URL: https://www.amazon.science/publications/human-body-measurement-estimation-with-adversarial-augmentation
      AuthorName: Nataniel Ruiz, Miriam Bellver, Timo Bolkart, Ambuj Arora, Ming C. Lin, Javier Romero and Raja Bala