Pose Guided Attention for Multi-Label Fashion Image Classification

Beatriz Quintino Ferreira, Joao P. Costeira, Ricardo G. Sousa, Liang-Yan Gui, Joao P. Gomes; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 0-0

Abstract


We propose a compact framework with guided attention for multi-label classification in the fashion domain. Our visual semantic attention model (VSAM) is supervised by automatic pose extraction creating a discriminative feature space. VSAM outperforms the state of the art for an in-house dataset and performs on pair with previous works on the DeepFashion dataset, even without using any landmark annotations. Additionally, we show that our semantic attention module brings robustness to large quantities of wrong annotations and provides more interpretable results.

Related Material


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[bibtex]
@InProceedings{Ferreira_2019_ICCV,
author = {Quintino Ferreira, Beatriz and Costeira, Joao P. and Sousa, Ricardo G. and Gui, Liang-Yan and Gomes, Joao P.},
title = {Pose Guided Attention for Multi-Label Fashion Image Classification},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops},
month = {Oct},
year = {2019}
}