Year: 2020
Type: Proceeding article
Title: Object detection and semantic segmentation of fashion images
Author: Sandra Treneska
Author: Sonja Gievska
Abstract: Over the past few years, fashion brands have been rapidly implementing computer vision into the fashion industry. Our research objective was to analyse a number of methods suitable for object detection and segmentation of apparel in fashion images. Two types of models are proposed. The first, simpler, is a convolutional neural network used for object detection of clothing items on the Fashion-MNIST dataset and the second, more complex Mask R-CNN model is used for object detection and instance segmentation on the iMaterialist dataset. The performance of the first proposed model reached 93% accuracy. Furthermore, the results from the Mask R-CNN model are visualized.
Publisher: Ss Cyril and Methodius University in Skopje, Faculty of Computer Science and Engineering, Republic of North Macedonia
Relation: CIIT 2020 short papers;6
Identifier: oai:repository.ukim.mk:20.500.12188/8182
Identifier: http://hdl.handle.net/20.500.12188/8182
