A dual-axis taxonomy classifies image degradations by causal source and perceptual effect, with a severity quantification layer using standard quality metrics, demonstrated via a COCO-based object detector robustness benchmark.
Making a “completely blind
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A survey categorizing weather restoration methods for smart transportation into traditional priors, CNNs, transformers, diffusion models, and VLMs, with discussions on datasets, night-time challenges, and future directions.
citing papers explorer
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A Causally Grounded Taxonomy for Image Degradation Robustness Evaluation
A dual-axis taxonomy classifies image degradations by causal source and perceptual effect, with a severity quantification layer using standard quality metrics, demonstrated via a COCO-based object detector robustness benchmark.
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Clear Roads, Clear Vision: Advancements in Multi-Weather Restoration for Smart Transportation
A survey categorizing weather restoration methods for smart transportation into traditional priors, CNNs, transformers, diffusion models, and VLMs, with discussions on datasets, night-time challenges, and future directions.