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Perceptual loss compares images in a deep network's feature space rather than raw pixels, which aligns better with human judgment of similarity.
A real symmetric matrix A is positive definite if and only if x^T A x > 0 for every nonzero vector x, and positive semidefinite if x^T A x ≥ 0.