A facial attribute editing method combining multi-attention and IE-GAN
Face attribute editing has two main purposes:① to transform the image from the source domain to the target domain and make changes to the specified target attributes(such as gender,age,hair color,etc.);② to change only the face regions related to the target attributes and retain the details of other attributes outside the target attributes.And the existing face attribute editing methods inevitably make changes to the regions unrelated to the target attributes.Therefore,a face attribute editing method MAIE-GAN based on IE-GAN and multi-attention mechanism is proposed,introducing the concept of complementary attention connection(CAC)to connect codecs,solving the information redundancy problem caused by direct jump connection,the self-attention mechanism is used as a complement to the convelutional layer in the generator to enable better localisation of the target attributes and confinement of the attribute transformation region,in addition to using the concept of complementary attention features to achieve better retention of irrelevant regions of the target attributes.A comparative analysis with existing methods shows that this method outperforms existing methods in terms of attribute localization and image quality.
NETL
NSTL
万方数据
