Closed haoming-codes closed 3 years ago
Hi, Thanks a lot for your interest in our work. Regarding your question, I suggest printing some generated images during training (e.g. print some images for some ages every 1000 iterations). If the image quality gradually improves, the training should be okay. Sometimes the d loss and g loss are not very informative. Hopefully, it can help. Please let me know if there are any other issues. Best,
Xin
Dear authors of CcGAN, thank you for sharing the code! I'm running CcGAN Hard in
improved_CcGAN/UTKFace/UTKFace_64x64/CcGAN/scripts/run_train.sh
(which hopefully is the setting used in the paper) directly in Google Colab, and observe that g_loss and d_loss (logged here) stays about constant (at about .8 and 1.3, respectively) throughout the 40,000 iterations. Is this the expected behavior?