Generative Modelling of Semantic Segmentation Data in the Fashion Domain
Authors: Marie Korneliusson, John Martinsson, Olof Mogren
Published in: Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019
Year: 2020
Location:
Abstract
In this work, we propose a method to generatively model the joint distribution of images and corresponding semantic segmentation maps using generative adversarial networks. We extend the Style-GAN architecture by iteratively growing the network during training, to add new output channels that model the semantic segmentation maps. We train the proposed method on a large dataset of fashion images and our experimental evaluation shows that the model produces samples that are coherent and plausible with semantic segmentation maps that closely match the semantics in the image.
BibTeX
@InProceedings{Korneliusson_2019_ICCV,
author = {Korneliusson, Marie and Martinsson, John and Mogren, Olof},
title = {Generative Modelling of Semantic Segmentation Data in the Fashion Domain},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops},
month = {Oct},
year = {2019}
}
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