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Perceptual Loss

A loss function based on differences in intermediate-layer features of a pretrained feature-extraction network. It optimizes the texture and semantic similarity of reconstructed images rather than per-pixel error, and is commonly used in super-resolution and image restoration.

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Oct 21

The perceptual loss was proposed by Johnson et al.; it feeds the reconstructed image and the real image into a pretrained feature extraction network and compares differences in intermediate-layer feature maps.

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