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SelfLift: Accelerating Few-Step Diffusion via Self-Recovering Resolution Transition
Few-step diffusion models substantially compress temporal computation, making the spatial cost of each model evaluation an increasingly dominant source of inference latency. Progressive-resolution inference reduces this cost by performing early denoising at low resolution and reserving high-resoluti
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