PhotoArt50

by Ravi Kiran Sarvadevabhatla,Shiv Surya,Srinivas S S Kruthiventi,Venkatesh Babu RUnknown

PhotoArt50

The Photo-Art-50 dataset is a dataset of images from photos and artwork, with ground truth bounding boxes for 50 object classes. The aim is to evaluate cross-depiction object detection performance. This dataset contains 50 classes of object. There are 90 to 138 images for each class, approximately half of which are photos and the other half art. The 50 classes all appear in Caltech-256. Some of the photos are from Caltech-256; the rest are from Google searches. The artwork images came from searching using a variety of keywords to cover a wide gamut of depiction styles, e.g. "horse cartoon", "horse drawing", "horse painting", "horse sketches", "horse kid drawing", etc. All selected images have a reasonable size of a meaningful object area and there are ground-truth bounding boxes, labelled by hand, for each object. The dataset was originally produced by Qi Wu and Hongping Cai while working under Peter Hall at the University of Bath.

Dataset Attributes

Label SVG
TasksDetection
Label SVG
CategoriesArtwork