journal article·2021-09-01

Clothing Color Collocation with Deep Neural Networks

Cheng Zhang, Xiaodong Yue, Chengyue Yu, Zhiye Wang

AATCC Journal of Research· Volume 8· Issue 1_suppl
Publisher page

Abstract

Color is the foundation of well-put-together ensembles in clothing collocation. The way people coordinate and match different hues within looks may bring different visual feelings. However, clothing color collocation is an extremely challenging task due to great changes of public tastes and differences of consciousness towards color collocation. We propose a clothing color collocation model that consists of two deep neural networks based on color histograms calculated from a quantized color space and design features from clothing images. Given a clothing collocation, the model produces a score that indicates the degree that these clothes match. Experiments on Polyvore409k data sets validate the proposed model for clothing color collocation.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Color Science and Applications · Image Enhancement Techniques · Color perception and design

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Shanghai University

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