Pose Guided Attention for Multi-Label Fashion Image Classification
Beatriz Quintino Ferreira, João Paulo Costeira, Ricardo Sousa, Liang-Yan Gui, João Pedro Gomes · 2019
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.