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.
The paper reports roughly log-linear PSNR gains and a 50-category CDD-50 benchmark.
The small variant uses a frozen Tiny-VAE and Terminal Velocity Matching at 34 GFLOPs and one function evaluation.
RAESR restores images in a frozen DINOv3-L latent space, leading reported super-resolution quality and speed.
ImIR replaces text prompts with image-derived instructions so one Qwen adapter restores many degradations.
UniH3 unifies hierarchical homogeneity and heterogeneity modeling for all-in-one medical image restoration across modalities and degradation types.
Mi-Ripple is a diagnosis-guided restoration workflow that removes digital ripple artifacts introduced by iterative AI image editing while preserving structure.

Google DeepMind and filmmakers used generative image restoration and performance capture to recreate a couple's unrecorded past in the documentary 'Love, Rendered'.
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