UDAIR combines codebook quantization, cross-sample contrastive learning, and CORAL-based test-time adaptation to reduce the domain gap in all-in-one image restoration.
Vision language models in au- tonomous driving: A survey and outlook,
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From Controlled Scenarios to Real-World: Cross-Domain Degradation Pattern Matching for All-in-One Image Restoration
UDAIR combines codebook quantization, cross-sample contrastive learning, and CORAL-based test-time adaptation to reduce the domain gap in all-in-one image restoration.