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Diffusion models can achieve up to $6.9\times$ speedup by adaptively adjusting step sizes based on a staleness signal's "headroom," effectively jumping over scheduled inference steps.
By harnessing scene geometry, this method achieves significantly improved reflection consistency in mirror inpainting, outperforming conventional generative techniques.