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Research map / Image generation / Autoregressive and latent generation

Semantic Image Inpainting With Deep Generative Models

CVPR 2017 · Image generation › Autoregressive and latent generation · approach: Classical generative image synthesis · 1,226 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use Semantic Image Inpainting instead of Context EncoderSemantic image inpainting · CelebA, center maskPSNR (dB): 21.3 -> 19.4Hurt
Use Semantic Image Inpainting instead of Context EncoderSemantic image inpainting · SVHN, center maskPSNR (dB): 22.3 -> 19.0Hurt
Use Semantic Image Inpainting instead of Context EncoderSemantic image inpainting · Cars, center maskPSNR (dB): 14.1 -> 13.5Hurt
Use Semantic Image Inpainting instead of Context EncoderSemantic image inpainting · CelebA, pattern maskPSNR (dB): 19.2 -> 17.4Hurt
Use Semantic Image Inpainting instead of Context EncoderSemantic image inpainting · SVHN, pattern maskPSNR (dB): 22.3 -> 19.8Hurt
Use Semantic Image Inpainting instead of Context EncoderSemantic image inpainting · Cars, pattern maskPSNR (dB): 14.0 -> 14.1Helped
Use Semantic Image Inpainting instead of Context EncoderSemantic image inpainting · CelebA, random maskPSNR (dB): 20.6 -> 22.8Helped
Use Semantic Image Inpainting instead of Context EncoderSemantic image inpainting · SVHN, random maskPSNR (dB): 24.1 -> 33.0Helped
Use Semantic Image Inpainting instead of Context EncoderSemantic image inpainting · Cars, random maskPSNR (dB): 16.1 -> 18.9Helped
Use Semantic Image Inpainting instead of Context EncoderSemantic image inpainting · CelebA, half maskPSNR (dB): 15.5 -> 13.7Hurt
Use Semantic Image Inpainting instead of Context EncoderSemantic image inpainting · SVHN, half maskPSNR (dB): 19.1 -> 14.6Hurt
Use Semantic Image Inpainting instead of Context EncoderSemantic image inpainting · Cars, half maskPSNR (dB): 12.6 -> 11.1Hurt

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