Fashion is Taking Shape: Understanding Clothing Preference Based on Body Shape From Online Sources
This work addresses the problem of personalized fashion recommendations based on body shape for consumers and retailers, though it appears incremental as it builds on existing shape estimation techniques.
The researchers tackled the problem of understanding how clothing preferences correlate with body shape by collecting a new dataset (Fashion Takes Shape) and developing a multi-photo approach to estimate body shapes. They demonstrated that clothing categories and body shapes are correlated in real-world data, with their method leading to better predictive performance compared to single-view estimates or manual annotations.
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.