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Research map / Image generation / Editing and style transfer

EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations

NeurIPS 2022 · Image generation › Editing and style transfer · approach: Image-to-image translation · 70 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add energy guidance from source+target-domain feature extractors to SDEdit-style SDESDEdit · Cat->DogFID: 74.17 -> 65.82Helped
add energy guidanceSDEdit · Wild->DogFID: 68.51 -> 59.75Helped
add energy guidanceSDEdit · Male->FemaleFID: 49.43 -> 41.93Helped
add energy guidanceSDEdit · Cat->DogL2 distance: 47.88 -> 47.22Helped
increase lambda_s (realism expert) from 0 to 500 (ablation)EGSDE · Cat->DogFID: 73.85 -> 62.44Helped
increase lambda_s from 0 to 500 (ablation)EGSDE · Cat->DogL2 distance: 47.87 -> 51.02Hurt
increase lambda_i (faithful expert) from 0 to 2 (ablation)EGSDE · Cat->DogL2 distance: 47.87 -> 44.23Helped
increase lambda_i from 0 to 2 (ablation)EGSDE · Cat->DogFID: 73.85 -> 77.05Hurt
use energy on perturbed source x_t instead of noise-free x0 (ablation)EGSDE · Cat->DogFID: 79.01 -> 65.82Helped
use energy on perturbed source x_t instead of noise-free x0 (ablation)EGSDE · Male->FemaleFID: 41.86 -> 41.93No clear effect
increase initial time M from 0.3T to 0.7T (ablation)EGSDE · Cat->DogFID: 97.02 -> 53.01Helped
increase initial time M from 0.3T to 0.7T (ablation)EGSDE · Cat->DogL2 distance: 33.39 -> 65.61Hurt

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