Segmentation task for fashion and apparel

• URL: http://arxiv.org/abs/2006.11375v1
• Date: Sun, 14 Jun 2020 03:44:58 GMT
• Title: Segmentation task for fashion and apparel
• Authors: Hassler Castro and Mariana Ramirez
• Abstract summary: Globalization has brought fast fashion, quick shifting consumer shopping preferences, more competition, and abundance in fashion shops and retailers. This paper implements several Deep Learning Architectures using the iMaterialist dataset consisting of 45,000 images with 46 different clothing and apparel categories.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The Fashion Industry is a strong and important industry in the global economy. Globalization has brought fast fashion, quick shifting consumer shopping preferences, more competition, and abundance in fashion shops and retailers, making it more difficult for professionals in the fashion industry to keep track of what fashion items people wear and how they combine them. This paper solves this problem by implementing several Deep Learning Architectures using the iMaterialist dataset consisting of 45,000 images with 46 different clothing and apparel categories.

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