banikr:

Shall I normalize both input and output from [-1,1] and train the network?


I would start by standardizing the input (zero mean, unit variance) similar to the preprocessing pipeline for images.
Regarding the target, I would also start by normalizing it to e.g. [0, 1] and check both outputs.
Could you run a small test by printing the mean value of the first input training sample and the first validation sample as well as the mean values of the outputs of your model for these targets?
The discrepancy between these losses is so huge, that I would assume a total domain mismatch.