Consistent-Inversion introduces reverse consistency guidance that corrects early target denoising steps by checking reversibility toward the source inversion trajectory under the original prompt.
Negative-prompt inversion: Fast image inversion for editing with text-guided diffusion models
4 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 4representative citing papers
DRFS is a new inversion-free editing technique for rectified flow models that models source-target velocity discrepancies and applies a time-dependent shift to improve fidelity and unify prior methods like DDS and FlowEdit.
SelFix selects straighter-trajectory fixed-point solutions for rectified flow inversion to improve real-image reconstruction and source-preserving editing.
TFinv proposes iterative noise alignment and suffix learning to enable training-free inversion and editing for one-step diffusion models, achieving SOTA performance and higher efficiency than multistep methods.
citing papers explorer
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Consistent-Inversion: Reverse Consistency Guidance for Structure-Preserving Visual Editing
Consistent-Inversion introduces reverse consistency guidance that corrects early target denoising steps by checking reversibility toward the source inversion trajectory under the original prompt.
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Delta Rectified Flow Sampling for Text-to-Image Editing
DRFS is a new inversion-free editing technique for rectified flow models that models source-target velocity discrepancies and applies a time-dependent shift to improve fidelity and unify prior methods like DDS and FlowEdit.
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Root-Selecting Fixed-Point Inversion for Rectified Flows via Trajectory Straightness
SelFix selects straighter-trajectory fixed-point solutions for rectified flow inversion to improve real-image reconstruction and source-preserving editing.
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Training-free image inversion for one-step diffusion models
TFinv proposes iterative noise alignment and suffix learning to enable training-free inversion and editing for one-step diffusion models, achieving SOTA performance and higher efficiency than multistep methods.