PT Unknown
AU Lu Yu
   Yongmei Cheng
   Joost Van de Weijer
TI Weakly Supervised Domain-Specific Color Naming Based on Attention
BT 24th International Conference on Pattern Recognition
PY 2018
BP 3019
EP 3024
DI 10.1109/ICPR.2018.8545222
AB The majority of existing color naming methods focuses on the eleven basic color terms of the English language. However, in many applications, different sets of color names are used for the accurate description of objects. Labeling data to learn these domain-specific color names is an expensive and laborious task. Therefore, in this article we aim to learn color names from weakly labeled data. For this purpose, we add an attention branch to the color naming network. The attention branch is used to modulate the pixel-wise color naming predictions of the network. In experiments, we illustrate that the attention branch correctly identifies the relevant regions. Furthermore, we show that our method obtains state-of-the-art results for pixel-wise and image-wise classification on the EBAY dataset and is able to learn color names for various domains.
ER