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WeatherProof Dataset Challenge

Updated 5 July 2026
  • WeatherProof Dataset Challenge is a paired benchmark for semantic segmentation on clear vs. adverse-weather images, enabling controlled evaluation of weather effects.
  • It covers rain, fog, and snow with high-quality pixel-level labels for 10 semantic classes, using real imagery from diverse global locations.
  • The challenge employs paired testing protocols, consistency losses, and language guidance to enhance robustness and reduce performance gaps in adverse conditions.

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