iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press
Hi there! You said you fine-tuned the pre-trained RBPN for 4 epochs. I was curious about the values of Generator and Discriminator loss and their behavior. Do they follow the SRGAN? Also, how did you decide to fine-tune it for 4 epochs? By observing losses and evaluation set scores?
Hi there! You said you fine-tuned the pre-trained RBPN for 4 epochs. I was curious about the values of Generator and Discriminator loss and their behavior. Do they follow the SRGAN? Also, how did you decide to fine-tune it for 4 epochs? By observing losses and evaluation set scores?