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Fashion Is Taking Shape: Understanding Clothing Preference Based on Body Shape From Online Sources

机译:时尚正在塑造:了解基于身体形状的服装偏好来自在线来源

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To study the correlation between clothing garments and body shape, we collected a new dataset (Fashion Takes Shape), which includes images of female users with clothing category annotations. Despite the progress in body shape estimation from images, it turns out to be challenging to infer body shape from such diverse, real-world photos. Hence, we propose a novel and robust multi-photo approach to estimate body shapes of each user and build a conditional model of clothing categories given body-shape. We demonstrate that in real-world data, clothing categories and body-shapes are correlated and show that our multi-photo approach leads to a better predictive model for clothing categories compared to models based on single-view shape estimates or manually annotated body types. We see our method as the first step towards the large-scale understanding of clothing preferences from body shape.
机译:为研究服装服装与体形之间的相关性,我们收集了一个新的数据集(时尚呈现形式),其中包括带有服装类别注释的女性用户的图像。尽管身体形状估计从图像中进行了进展,但事实证明,从这种多样化的世界照片中推断身体形状是挑战。因此,我们提出了一种新颖且坚固的多重照片方法来估计每个用户的身体形状,并构建给定体形的服装类别的条件模型。我们证明,在现实世界的数据中,与基于单视图形状估计或手动注释的身体类型的型号相比,我们的多拍摄方法和身体形状有关,并表明我们的多照片方法导致了与服装类别更好的预测模型。我们认为我们的方法是迈向朝着身体形状的衣物偏好的大规模了解的第一步。

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