Abstract: In one implementation of remote apparel fitting and garment layering, a processing device determines a digital representation of a subject person wearing a first clothing item. The digital representation is generated using a machine-learning model based on an image of a subject person and a selection of the first clothing item via a user interface. The digital representation is presented via a display. The processing device then receives, via a user interface, a selection of a second clothing item to remotely try on in combination with the first clothing item. The processing device uses the machine-learning model to display an updated digital representation of the subject person wearing the first clothing item layered with the second clothing item.

Abstract: In one implementation of remote apparel fitting, a processing device receives an input image that depicts a subject person (e.g., an online consumer). A selection of a clothing item is also received. For example, the subject person is browsing an online catalog of clothing items to find clothing items (e.g., shirts) that fit well. A machine-learning model uses the image to determine measurements of the subject person that correlate to one or more dimensions of the clothing item. In some implementations, the machine-learning model determines the measurements after generating a mesh model of the subject person. The machine-learning model is then used to determine the fit of the clothing item on the subject person. The processing device then presents a composite image that represents the fit of the clothing item on the subject person overlayed on a reproduced image of the subject person wearing the clothing item.