Flow Straight to Reality: Perceptually Consistent Flow Matching for Efficient Image Restoration
Image restoration is fundamentally constrained by the tradeoff between distortion and perception: minimizing pixel-wise error yields over-smoothed results, whereas optimizing for perceptual realism often introduces structural deviations. Recent approaches attempt to balance this tradeoff via posterior sampling or multi-stage generative pipelines, yet remain computationally expensive and architecturally complex. To overcome these limitations, we propose PCFlow (Perceptually Consistent Flow Matching), a unified framework that directly parameterizes a continuous transport from degraded observations to clean targets, jointly optimizing distortion and perceptual quality. While its latent consi...
| Authors | Sangwoo Jo, Donggeun Ko, Jayeon Kang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 11 August 2026 |
| Last updated at source | 11 August 2026 |
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