AGA-GAN: Attribute Guided Attention Generative Adversarial Network with U-Net for face hallucination

作者：

Highlights：

• AGA-GAN uses facial descriptors to generate high-resolution facial images.

• Performance increases with additional information about features like facial hair.

• Coupling AGA-GAN with UNet gives superior hallucination results.

• AGA-GAN and AGA-GAN+UNet, both translate well on downstream face verification tasks.

摘要

•AGA-GAN uses facial descriptors to generate high-resolution facial images.•Performance increases with additional information about features like facial hair.•Coupling AGA-GAN with UNet gives superior hallucination results.•AGA-GAN and AGA-GAN+UNet, both translate well on downstream face verification tasks.

论文关键词：Face hallucination,Generative adversarial network,U-Net,Spatial attention

论文评审过程：Received 14 November 2021, Revised 4 August 2022, Accepted 8 August 2022, Available online 18 August 2022, Version of Record 7 September 2022.

论文官网地址：https://doi.org/10.1016/j.imavis.2022.104534