The purpose of this repo is to understand better the paper and do also some experiments with code.
The paper name is "𝑻𝒐𝒘𝒂𝒓𝒅𝒔 𝑹𝒆𝒂𝒍-𝑾𝒐𝒓𝒍𝒅 𝑩𝒍𝒊𝒏𝒅 𝑭𝒂𝒄𝒆 𝑹𝒆𝒔𝒕𝒐𝒓𝒂𝒕𝒊𝒐𝒏 𝒘𝒊𝒕𝒉 𝑮𝒆𝒏𝒆𝒓𝒂𝒕𝒊𝒗𝒆 𝑭𝒂𝒄𝒊𝒂𝒍 𝑷𝒓𝒊𝒐𝒓". It was published on 11 Jan 2021 by: Xintao Wang, Yu Li, Honglun Zhang and Ying Shan.
This paper aims at recovering high-quality faces from the low-quality counterparts suffering from unknown degradation, such as low-resolution, noise, blur, compression artifacts etc.
GFP-GAN is comprised of a degradation removal module (U-Net) and a pretrained face GAN. To train the model it uses in total three losses: Adversarial Loss, Facial Component Loss and Identity Preserving Loss.