WG-VITON: Wearing-Guide Virtual Try-On for Top and Bottom Clothes
This addresses a specific challenge in virtual try-on for fashion applications, but appears incremental as it builds on existing multi-garment VITON methods.
The paper tackles the problem of variation in wearing style when simultaneously replacing top and bottom clothes in virtual try-on, introducing WG-VITON that uses an additional binary mask to control wearing styles, effectively generating images with complicated styles like partly tucking in the top.
Studies of virtual try-on (VITON) have been shown their effectiveness in utilizing the generative neural network for virtually exploring fashion products, and some of recent researches of VITON attempted to synthesize human image wearing given multiple types of garments (e.g., top and bottom clothes). However, when replacing the top and bottom clothes of the target human, numerous wearing styles are possible with a certain combination of the clothes. In this paper, we address the problem of variation in wearing style when simultaneously replacing the top and bottom clothes of the model. We introduce Wearing-Guide VITON (i.e., WG-VITON) which utilizes an additional input binary mask to control the wearing styles of the generated image. Our experiments show that WG-VITON effectively generates an image of the model wearing given top and bottom clothes, and create complicated wearing styles such as partly tucking in the top to the bottom