The content discusses the development of a controllable blind image decomposition network, CBDNet, to address diverse user needs in image restoration. The network allows users to selectively remove or retain specific components in images, improving efficiency and accuracy in blind image decomposition tasks. CBDNet excels in multi-degradation removal scenarios, showcasing its strong performance compared to existing methods. The study also introduces a challenging dataset with nine types of degradations for further research. Overall, CBDNet offers a robust solution for controllable blind image decomposition.
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by Zeyu Zhang,J... at arxiv.org 03-18-2024
https://arxiv.org/pdf/2403.10520.pdfDeeper Inquiries