PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator
CoRR(2024)
Abstract
We present Piecewise Rectified Flow (PeRFlow), a flow-based method for
accelerating diffusion models. PeRFlow divides the sampling process of
generative flows into several time windows and straightens the trajectories in
each interval via the reflow operation, thereby approaching piecewise linear
flows. PeRFlow achieves superior performance in a few-step generation.
Moreover, through dedicated parameterizations, the obtained PeRFlow models show
advantageous transfer ability, serving as universal plug-and-play accelerators
that are compatible with various workflows based on the pre-trained diffusion
models. The implementations of training and inference are fully open-sourced.
https://github.com/magic-research/piecewise-rectified-flow
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