A loss computed in auto-encoded space, instead of raw pixel space, improves the perception-distortion trade-off in GAN-based super-resolution by penalizing fidelity bias while preserving perceptual variance.
Toward real-world single image super-resolution: A new benchmark and a new model
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Auto-Encoded Supervision for Perceptual Image Super-Resolution
A loss computed in auto-encoded space, instead of raw pixel space, improves the perception-distortion trade-off in GAN-based super-resolution by penalizing fidelity bias while preserving perceptual variance.