IndoFashion: Apparel Classification for Indian Ethnic Clothes
CVPRW 2021 Oral - Computer Vision for Fashion, Art and Design Workshop
1Delft University of Technology
2Technical University of Munich
Abstract
Cloth categorization is an important research problem that is used by e-commerce websites for displaying correct products to the end-users. Indian clothes have a large number of clothing categories both for men and women. The traditional Indian clothes like "Saree" and "Dhoti" are worn very differently from western clothes like t-shirts and jeans. Moreover, the style and patterns of ethnic clothes have a very different distribution from western outfits. Thus the models trained on standard cloth datasets fail on ethnic outfits. We introduce the first large-scale ethnic dataset of over 106K images with 15 different categories for fine-grained classification of Indian ethnic clothes. We gathered a diverse dataset from a large number of Indian e-commerce websites. We then evaluate several baselines for the cloth classification task on our dataset. We obtain 88.43% classification accuracy. We hope that our dataset would foster research in the development of several algorithms such as cloth classification, landmark detection, especially for ethnic clothes.
SAREE
LEHENGA
WOMEN KURTA
DUPPATTA
GOWNS
NEHRU JACKETS
SHERWANIS
KURTA MEN
MEN MOJARI
LEGGINGS
SALWAR
BLOUSE
PALAZZO
DHOTI PANTS
PETTICOAT
WOMEN MOJARI
Dataset Details
Category-Wise Frequency Distribution of the Dataset
T-SNE Visualization
BibTeX
If you find this work useful for your research, please consider citing:
@InProceedings{Rajput_2021_CVPR,
author = {Rajput, Pranjal Singh and Aneja, Shivangi},
title = {IndoFashion: Apparel Classification for Indian Ethnic Clothes},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2021},
pages = {3935-3939}
}
If you have any questions, please contact us at indofashion.dataset@gmail.com