TY  - CONF
AU  - Vacit Oguz Yazici
AU  - Joost Van de Weijer
AU  - Arnau Ramisa
A2  - WORLDCIST
PY  - 2018//
TI  - Color Naming for Multi-Color Fashion Items
BT  - 6th World Conference on Information Systems and Technologies
SP  - 64
EP  - 73
VL  - 747
KW  - Deep learning
KW  - Color
KW  - Multi-label
N2  - There exists a significant amount of research on color naming of single colored objects. However in reality many fashion objects consist of multiple colors. Currently, searching in fashion datasets for multi-colored objects can be a laborious task. Therefore, in this paper we focus on color naming for images with multi-color fashion items. We collect a dataset, which consists of images which may have from one up to four colors. We annotate the images with the 11 basic colors of the English language. We experiment with several designs for deep neural networks with different losses. We show that explicitly estimating the number of colors in the fashion item leads to improved results.
UR  - https://doi.org/10.1007/978-3-319-77700-9_7
L1  - http://refbase.cvc.uab.es/files/YWR2018.pdf
N1  - LAMP; 600.109; 601.309; 600.120
ID  - Vacit Oguz Yazici2018
ER  -