1 code implementation • 27 May 2024 • Zhaoyang Sun, Shengwu Xiong, Yaxiong Chen, Yi Rong
This assumption allows CSD-MT to decouple the content and makeup style information in each face image through the frequency decomposition.
1 code implementation • 26 Apr 2023 • Yi Rong, Xiongbo Lu, Zhaoyang Sun, Yaxiong Chen, Shengwu Xiong
With this definition, the ESPT-augmented FSL objective promotes learning more transferable feature representations that capture the local spatial features of different images and their inter-relational structural information in each input episode, thus enabling the model to generalize better to new categories with only a few samples.
no code implementations • 7 Dec 2021 • 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.