Restore images with many defect types by using shared aspects across diverse degradations with DaAIR
Restore images with many defect types by using shared aspects across diverse degradations with DaAIR
Efficient Degradation-aware Any Image Restoration
arXiv paper abstract https://arxiv.org/abs/2405.15475
arXiv PDF paper https://arxiv.org/pdf/2405.15475
Project page https://eduardzamfir.github.io/daair
Reconstructing missing details from degraded low-quality inputs poses a significant challenge.
… large models capable of addressing … degradations simultaneously … these approaches introduce considerable computational overhead and complex learning paradigms
… propose DaAIR … All-in-One image restorer employing a Degradation-aware Learner (DaLe) in the low-rank regime to … mine shared aspects and … nuances across diverse degradations, generating a degradation-aware embedding.
By dynamically allocating model capacity to input degradations, … realize an efficient restorer integrating holistic and specific learning within a unified model.
Furthermore, DaAIR introduces a cost-efficient parameter update mechanism that enhances degradation awareness while maintaining computational efficiency.
… DaAIR outperforms both state-of-the-art All-in-One models and degradation-specific counterparts, affirming … efficacy and practicality …
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