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Cross-domain shoe image retrieval is a challenging problem, because the query photo from the street domain (daily life scenario) and the reference photo in the online domain (online shop images) have significant visual differences due to the viewpoint and scale variation, self-occlusion, and cluttered background. This paper proposes the semantic hierarchy of attribute convolutional neural network...
In this paper we deal with two image-based object search tasks in the fashion domain, clothing attribute prediction and cross-domain shoe retrieval. Clothing attribute prediction is about describing the appearances of clothes via semantic attributes and cross-domain shoe retrieval aims at retrieving the same shoe items from online stores given a daily life shoe photo. We jointly solve these two problems...
In this paper, we address the problem of matching the shoes from the daily life photos to exactly the same shoes from online shops. The problem is extremely challenging because of the significant visual differences between street domain images (shoe images captured in the daily life scenario) and online domain photos (images from online shops taken in the controlled environment). This paper presents...
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