Quantitative flow matching adapts denoising by estimating noise from pixel statistics and tuning the inference trajectory accordingly for better accuracy and efficiency across noise levels.
Flow matching for medical image synthesis: Bridging the gap between speed and quality
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Beyond Fixed Inference: Quantitative Flow Matching for Adaptive Image Denoising
Quantitative flow matching adapts denoising by estimating noise from pixel statistics and tuning the inference trajectory accordingly for better accuracy and efficiency across noise levels.