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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.
Flow matching learns a time-dependent vector field v_t(x, c) whose ODE transports simple noise to complex data, enabling fast, deterministic sampling.