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We present a novel approach that constructs 3D virtual garment models fromphotos. Unlike previous methods that require photos of a garment on a humanmodel or a mannequin, our approach can work with various states of the garment:on a model, on a mannequin, or on a flat surface. To construct a complete 3Dvirtual model, our approach only requires two images as input, one front viewand one back view. We first apply a multi-task learning network called JFNetthat jointly predicts fashion landmarks and parses a garment image intosemantic parts. The predicted landmarks are used for estimating sizinginformation of the garment. Then, a template garment mesh is deformed based onthe sizing information to generate the final 3D model. The semantic parts areutilized for extracting color textures from input images. The results of ourapproach can be used in various Virtual Reality and Mixed Reality applications.

3D Virtual Garment Modeling from RGB Images