DeblurFlow reformulates flow matching trajectories so the vector field matches the blur-to-clean residual, enabling LoRA-adapted pretrained flow models to perform blind motion deblurring with both high PSNR and perceptual quality.
Denoising diffusion probabilistic models.Advances in Neural Information Processing Systems (NeurIPS)
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Stochastic MeanFlow Policies enable one-step generative control in off-policy mirror descent by mapping noise through a MeanFlow transform, yielding tractable entropy and improved MuJoCo performance over Gaussian and generative baselines.
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Restoration-Aligned Generative Flow Models for Blind Motion Deblurring
DeblurFlow reformulates flow matching trajectories so the vector field matches the blur-to-clean residual, enabling LoRA-adapted pretrained flow models to perform blind motion deblurring with both high PSNR and perceptual quality.
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Stochastic MeanFlow Policies: One-Step Generative Control with Entropic Mirror Descent
Stochastic MeanFlow Policies enable one-step generative control in off-policy mirror descent by mapping noise through a MeanFlow transform, yielding tractable entropy and improved MuJoCo performance over Gaussian and generative baselines.