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Paper

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

MPS-Authors
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Sattar,  Hosnieh
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society;

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Pons-Moll,  Gerard
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society;

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Fritz,  Mario
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society;

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Fulltext (public)

1807.03235.pdf
(Preprint), 3MB

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There is no public supplementary material available
Citation

Sattar, H., Pons-Moll, G., & Fritz, M. (2018). Fashion is Taking Shape: Understanding Clothing Preference Based on Body Shape From Online Sources. Retrieved from http://arxiv.org/abs/1807.03235.


Cite as: http://hdl.handle.net/21.11116/0000-0001-B309-B
Abstract
To study the correlation between clothing garments and body shape, we collected a new dataset (Fashion Takes Shape), which includes images of users with clothing category annotations. We employ our 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.