Groups
Perceptual loss compares images in a deep network's feature space rather than raw pixels, which aligns better with human judgment of similarity.
Huber loss behaves like mean squared error (quadratic) for small residuals and like mean absolute error (linear) for large residuals, making it both stable and robust.