LipsFlower constrains flow matching to stabilize generative image restoration
LipHDiT uses spectral normalization, bounded modulation and finite-radius gain penalties, tested on blind face restoration.
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LipHDiT uses spectral normalization, bounded modulation and finite-radius gain penalties, tested on blind face restoration.
Design conditions treat network error as a bounded disturbance so feasibility and stability hold before deployment.
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