kawori
kawori
What causes this issue is that I normalized the images to the range [0, 1].
Solved. I'm using UNet for training, but it's hard to converge. It's the same for RedNet.
When using UNet, the loss decresed fast at first, but then decreased slowly and increased to INF suddenly.
I've create a repo here. You can review my codes though it's PyTorch implementation.
My UNet model has no BN and dropout layer. Its detailed parameters are from Noise2Noise paper's appendix.