ESRGAN (Enhanced Super-Resolution Generative Adversarial Network) is a deep learning model designed to enhance the resolution of images, producing high-quality, realistic textures. It builds upon the original SRGAN by introducing the Residual-in-Residual Dense Block (RRDB) without batch normalization, improving both network architecture and perceptual loss functions. This results in more natural and detailed images.
ESRGAN has been extended to Real-ESRGAN, which is trained with pure synthetic data to handle real-world image restoration tasks, such as removing JPEG compression artifacts.
For practical applications, ESRGAN has been utilized in texture enhancement for video games, significantly improving visual quality.
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