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Research map / Image generation / Editing and style transfer

IMAGINE: Image Synthesis by Image-Guided Model Inversion

CVPR 2021 · Image generation › Editing and style transfer · approach: Image-to-image translation · 28 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use image-guided classifier inversion with feature-distribution matching and adversarial patch training instead of DeepInversionImage synthesis from a single reference image · Object imagesIS: 68.5(5.0) -> 117.1(6.2)Helped
Use image-guided classifier inversion with feature-distribution matching and adversarial patch training instead of DeepInversionImage synthesis from a single reference image · Object imagesFID: 65.9(2.7) -> 38.3(1.1)Helped
Use image-guided classifier inversion with feature-distribution matching and adversarial patch training instead of DGPImage synthesis from a single reference image · Scene imagesIS: 12.7(0.6) -> 21.8(0.4)Helped
Use image-guided classifier inversion with feature-distribution matching and adversarial patch training instead of DGPImage synthesis from a single reference image · Scene imagesFID: 51.3(1.6) -> 47.3(0.9)Helped
Restrict feature matching to the three earliest layers, omitting the deepest layer (ablation)IMAGINE · Object imagessemantic consistency and image qualityHurt
Use single-stage optimization with nonzero feature-matching and adversarial weights instead of the two-stage schedule (ablation)IMAGINE · Image synthesisimage qualityNo clear effect

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