DVFace uses a spatio-temporal dual-codebook and asymmetric fusion in a one-step diffusion model to deliver better video face restoration quality, temporal consistency, and identity preservation than recent methods.
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VLM-IMI adapts VLMs with iterative and manual instructions plus a learnable fusion module to guide diffusion-based generative low-light image enhancement, outperforming prior methods in perceptual quality.
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DVFace: Spatio-Temporal Dual-Prior Diffusion for Video Face Restoration
DVFace uses a spatio-temporal dual-codebook and asymmetric fusion in a one-step diffusion model to deliver better video face restoration quality, temporal consistency, and identity preservation than recent methods.
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Adapting Large VLMs with Iterative and Manual Instructions for Generative Low-light Enhancement
VLM-IMI adapts VLMs with iterative and manual instructions plus a learnable fusion module to guide diffusion-based generative low-light image enhancement, outperforming prior methods in perceptual quality.