DAME-Net decouples explicit per-factor degradation perception from conditioned reconstruction via a Mixture-of-Experts architecture, achieving better compositional UAV image restoration than unified methods on the new MDUR benchmark with 43 degradation configurations.
Impact of adverse weather and image distortions on vision-based UA V detection: A performance evaluation of deep learning models,
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Compositional-Degradation UAV Image Restoration: Conditional Decoupled MoE Network and A Benchmark
DAME-Net decouples explicit per-factor degradation perception from conditioned reconstruction via a Mixture-of-Experts architecture, achieving better compositional UAV image restoration than unified methods on the new MDUR benchmark with 43 degradation configurations.