InverFill: One-Step Inversion for Enhanced Few-Step Diffusion Inpainting

ArXi:2603.23463v1 Announce Type: cross Recent diffusion-based models achieve photorealism in image inpainting but require many sampling steps, limiting practical use. Few-step text-to-image models offer faster generation, but naively applying them to inpainting yields poor harmonization and artifacts between the background and inpainted region. We trace this cause to random Gaussian noise initialization, which under low function evaluations causes semantic misalignment and reduced fidelity.