We present an automatically curated version of the Fashion144k dataset. In order to improve the quality of images, we annotated a small subset of images in which a single individual is roughly centered in the image as positive images. We then train a convolutional network in order to predict whether an image is positive or not, and use this network to automatically curate the rest of the dataset. Although this reduces the number of available images, the resulting images are of much higher quality and do not include product nor heavily distorted images.
For the dataset this builds on, please see Fashion144k.
If you use this dataset, please cite
@InProceedings{SimoSerraCVPR2015,
author = {Edgar Simo-Serra and Sanja Fidler and Francesc Moreno-Noguer and Raquel Urtasun},
title = {{Neuroaesthetics in Fashion: Modeling the Perception of Fashionability}},
booktitle = "Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR)",
year = 2015,
}