ST-VTON: Self-supervised vision transformer for image-based virtual try-on

Zheng Chong, Lingfei Mo

Abstract: Highlights•We propose a novel ViT-backed try-on method with lightweight preprocessing and a standard ViT without elaborate modification.•.We introduce a two-stage self-supervised training method which can expand paired try-on datasets from separate person images.•Our model can achieve competitive results for both paired try-on and unpaired clothing transfer.