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

机译:时尚正在形成:从在线资源中了解基于身体形态的服装偏好

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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:为了研究服装与体形之间的相关性,我们收集了一个新的数据集(Fashion Takes Shape),其中包括带有服装类别注释的女性用户图像。尽管从图像估计身体形状方面取得了进展,但从如此多样的真实照片中推断出身体形状仍然是一项挑战。因此,我们提出了一种新颖而强大的多照片方法来估计每个用户的身体形状,并根据给定的身体形状来建立服装类别的条件模型。我们证明,在现实世界的数据中,服装类别和身材是相关的,并且表明与基于单视图形状估计或手动标注的身体类型的模型相比,我们的多张照片方法可以为服装类别带来更好的预测模型。我们认为我们的方法是从体形全面了解服装偏好的第一步。

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