I am training a network that performs stereo depth estimation from a stereo pair. The training loss of my network is decreasing as expected but my testing loss and errors are increasing.
Is this considered as overfitting? I have included random cropping and normalizing my input images. Also, I included weight decay of 0.01 and my learning rate is 0.0005. I am running out of idea what could possibly be wrong. My network has a total of 4120322 parameters and all are convolutional layers with batch norms and relu except the last layer.