Facial attribute editing aims to manipulate attributes on the human face,
e.g., adding a mustache or changing the hair color. Existing approaches suffer
from a serious compromise between correct attribute generation and preservation
of the other information such as identity and background, because they edit the
attributes in the imprecise area. To resolve this dilemma, we propose a
progressive attention GAN (PA-GAN) for facial attribute editing. In our
approach, the editing is progressively conducted from high to low feature level
while being constrained inside a proper attribute area by an attention mask at
each level. This manner prevents undesired modifications to the irrelevant
regions from the beginning, and then the network can focus more on correctly
generating the attributes within a proper boundary at each level. As a result,
our approach achieves correct attribute editing with irrelevant details much
better preserved compared with the state-of-the-arts. Codes are released at
this https URL

本文提出了一种基于渐进式注意力 GAN 的人脸属性编辑方法，通过每个级别的注意力掩模约束在适当的属性区域内，从高到低的特征级别逐步进行编辑，以维护身份和背景等其他信息，并避免不必要的修改干扰，使该方法实现了正确的人脸属性编辑，并更好地保留了不相关的细节信息。