PG-3DVTON: Pose-Guided 3D Virtual Try-on Network

Sanaz Sabzevari, Ali Ghadirzadeh, Mårten Björkman, Danica Kragic

Abstract: Virtual try-on (VTON) eliminates the need for in-store trying of garments by enabling shoppers to wear clothes digitally. For successful VTON, shoppers must encounter a try-on experience on par with in-store trying. We can improve the VTON experience by providing a complete picture of the garment using a 3D visual pre-sentation in a variety of body postures. Prior VTON solutions show promising results in generating such 3D presentations but have never been evaluated in multi-pose settings. Multi-pose 3D VTON is particularly challenging as it often involves tedious 3D data collection to cover a wide variety of body postures. In this paper, we aim to develop a multi-pose 3D VTON that can be trained without the need to construct such a dataset. Our framework aligns in-shop clothes to the desired garment on the target pose by optimizing a consistency loss. We address the problem of generating fine details of clothes in different postures by incorporating multi-scale feature maps. Besides