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Video Colorization with Pre-trained Text-to-Image Diffusion Models
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2026-02-26 04:33:21
raw text
Video Colorization with Pre-trained Text-to-Image Diffusion Models Video Colorization with Pre-trained Text-to-Image Diffusion Models Anonymous Authors arXiv Code (coming soon) Abstract Video colorization is a challenging task that involves inferring plausible and temporally consistent colors for grayscale frames. In this paper, we present ColorDiffuser, an adaptation of a pre-trained text-to-image latent diffusion model for video colorization. With the proposed adapter-based approach, we repropose the pre-trained text-to-image model to accept input grayscale video frames, with the optional text description, for video colorization. To enhance the temporal coherence and maintain the vividness of colorization across frames, we propose two novel techniques: the Color Propagation Attention and Alternated Sampling Strategy . Color Propagation Attention enables the model to refine its colorization decision based on a reference latent frame, while Alt...
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