2 citations · 4 across the 6 of their papers we have counts for
7 papers
RealisID: Scale-Robust and Fine-Controllable Identity Customization via Local and Global Complementation
Zhaoyang Sun, Fei Du, Weihua Chen +4
Recently, the success of text-to-image synthesis has greatly advanced the development of identity customization techniques, whose main goal is to produce realistic identity-specifi…
SHMT: Self-supervised Hierarchical Makeup Transfer via Latent Diffusion Models
Zhaoyang Sun, Shengwu Xiong, Yaxiong Chen +4
This paper studies the challenging task of makeup transfer, which aims to apply diverse makeup styles precisely and naturally to a given facial image. Due to the absence of paired…
Content-Style Decoupling for Unsupervised Makeup Transfer without Generating Pseudo Ground Truth
Zhaoyang Sun, Shengwu Xiong, Yaxiong Chen +1
The absence of real targets to guide the model training is one of the main problems with the makeup transfer task. Most existing methods tackle this problem by synthesizing pseudo…
ESPT: A Self-Supervised Episodic Spatial Pretext Task for Improving Few-Shot Learning
Yi Rong, Xiongbo Lu, Zhaoyang Sun +2
Self-supervised learning (SSL) techniques have recently been integrated into the few-shot learning (FSL) framework and have shown promising results in improving the few-shot image…
SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal
Zhaoyang Sun, Yaxiong Chen, Shengwu Xiong
Makeup transfer is not only to extract the makeup style of the reference image, but also to render the makeup style to the semantic corresponding position of the target image. Howe…
Local Facial Makeup Transfer via Disentangled Representation
Zhaoyang Sun, Wenxuan Liu, Feng Liu +2
Facial makeup transfer aims to render a non-makeup face image in an arbitrary given makeup one while preserving face identity. The most advanced method separates makeup style infor…