Skip to content
Artwork containing people for academic use only
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
Annotations
JPEGImages
README.md
citation.bib
version

README.md

#People-Art dataset

The People-Art dataset is a dataset of images from photos and artwork, with ground truth bounding boxes for people. The aim is to address the problem of detecting objects in images other than photographs. The reason for labelling people is that (we observe that) they occur more frequently than any other class.

The dataset contains the following:

  • Images divided into 43 depiction styles: 41 styles are from WikiArt.org; photos are from PASCAL VOC 2012; cartoons from google searches.
  • Labellings of people compatible with PASCAL VOC format, with some differences (see below)

The dataset was originally produced by Hongping Cai and Qi Wu while working under Peter Hall at the University of Bath.

Labellings

The labellings of people are compatible with PASCAL VOC format except for the following differences:

  • The list of images is in the Annotations directory, as people_{train/val/test/trainval}.txt e.g. Annotations/people_train.txt. All images are either positive (at least one person) or negative (no people present)
  • Images and Annotations lie in a sub-directory, e.g. JPEGImages/Cubism/pablo-picasso_algerian-women-delacroix-1955.jpg and Annotations/Cubism/pablo-picasso_algerian-women-delacroix-1955.jpg.xml
  • Only images which are positive have xml annotation files

Copyright

Many of the images are subject to copyright. These are provided only for "data mining for non-commercial research" or other "fair dealing" (UK Guidance).

Publications

The dataset v2 features in The Cross-Depiction Problem: Computer Vision Algorithms for Recognising Objects in Artwork and in Photographs (arXiv pre-print) and You only look once: Unified, real-time object detection (arXiv pre-print).

The dataset v2.1 features in Detecting People in Artwork with CNNs.

If you wish to cite the dataset, please use the following citation.

You can’t perform that action at this time.