Few-Step Generation
A research direction focused on accelerating sampling in diffusion models by compressing the number of sampling steps from hundreds to just a few, thereby improving generation efficiency. The central challenge is maintaining generation quality while reducing the number of steps.
Core Facts
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When the sampling process is compressed into a small number of coarse-grained transition steps, simple Gaussian denoising cannot accurately characterize the true reverse process
All Facts (2)
Consistency models attempt to compress the multi-step denoising process of diffusion models into 1–4 steps, theoretically capable of improving inference speed by 10–50 times.
75%UnverifiedWhen the sampling process is compressed into a small number of coarse-grained transition steps, simple Gaussian denoising cannot accurately characterize the true reverse process
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