The Generative Models have gained considerable attention in unsupervised learning via a
new and practical framework called Generative Adversarial Networks (GAN) due to their …

The fashion industry is on the verge of an unprecedented change. The implementation of
machine learning, computer vision, and artificial intelligence (AI) in fashion applications is …

Blind image deblurring (BID) remains a challenging and significant task. Benefiting from the
strong fitting ability of deep learning, paired data-driven supervised BID methods have …

Makeup transfer is the task of applying on a source face the makeup style from a reference
image. Real-life makeups are diverse and wild, which cover not only color-changing but also …

In this paper, we propose a region adaptive makeup transfer GAN, called RamGAN, for
precise region-level makeup transfer. Compared to face-level transfer methods, our …

Fashion, as a popular aesthetic expression, is often conveyed in a specific context, in
particular in clothing, footwear, and accessories. Attributed to its enormous economic …

Due to their excellent performance on aggregating global features, Transformer structures
are being widely employed in deep learning-based visual object tracking algorithms …

The purpose of makeup transfer (MT) is to transfer makeup from a reference image to a
target face while preserving the target's content. Existing methods have made remarkable …

While existing makeup style transfer models perform an image synthesis whose results
cannot be explicitly controlled, the ability to modify makeup color continuously is a desirable …

This paper focuses on the real-world automatic makeup problem. Given one non-makeup
target image and one reference image, the automatic makeup is to generate one face …