A convolutional neural network trained to distinguish between "real" high-resolution images and those "faked" by the generator.
Combined loss involving Content Loss (based on feature maps from a pre-trained VGG19 model) and Adversarial Loss . 3. Implementation Details srganzo1.rar
Most SRGAN implementations use PyTorch or TensorFlow/TensorLayer . srganzo1.rar
Discuss the trade-off between (Peak Signal-to-Noise Ratio) and Perceptual Quality . While SRGANs might have lower PSNR, they look much better to the human eye. srganzo1.rar