yes the centering “might” be learnt by the bias term, if all stars align (and your biases are closely initialized). Giving a centering prior based on dataset statistics just helps. Scaling can also technically be learnt by the convolution operation (the weights can learn to scale up or down), but whether the weights can learn good scaling depends on initialization, how activation dynamic range changes over the network depth etc.