Garment Detection in Catwalk Videos

Qi Dang, Heydar Afkham, Oskar Juhlin

2021

Abstract

Most computer vision applications in the commercial scene lack a large scale and properly annotated dataset. The solution to these applications relies on already published code and knowledge transfer from existing computer vision datasets. In most cases, these applications sacrifice proper benchmarking of the solution and rely on the performance of used methods from their respective papers. In this paper, we are focusing on how we can use the existing code base and the datasets in computer vision to address a hypothetical application of detecting garments in the catwalk videos. We proposed a combination of methods that allows us to localize garments in complex scenery by only training models on public datasets. To understand which method performs best for our application, we have designed a relative-benchmark framework that requires very little manual annotation to work.

Paper Citation

in Harvard Style

Dang Q., Afkham H. and Juhlin O. (2021). Garment Detection in Catwalk Videos.In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-486-2, pages 471-479. DOI: 10.5220/0010192804710479

in Bibtex Style

@conference{icpram21,
author={Qi Dang and Heydar Afkham and Oskar Juhlin},
title={Garment Detection in Catwalk Videos},
booktitle={Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2021},
pages={471-479},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010192804710479},
isbn={978-989-758-486-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Garment Detection in Catwalk Videos
SN - 978-989-758-486-2
AU - Dang Q.
AU - Afkham H.
AU - Juhlin O.
PY - 2021
SP - 471
EP - 479
DO - 10.5220/0010192804710479