Super-Resolution Generative Adversarial Networks Loss Function For Gen loss [optional] VGG19 BottleNeck feature loss (content loss) MSE loss (content loss) Adversarial GAN loss with sigmoid For Disc loss Adversarial GAN loss with sigmoid Architecture Networks Same as SRGAN paper DIFFS SRGAN Paper ME Weight initializer normal dist HE initializer image scaling LR[0,1] HR[-1,1] L/HR[-1,1] G loss content loss with vgg19 just MSE global steps 2e5 1e5 Tensorboard Elapsed time : 1d 9h 30m 52s with GTX Titan X 12GB x 1 (maxwell) Result VALID HR image VALID LR image Global Step 10k Global Step 25k Global Step 55k To-Do Not good performance... on-editing...
