AIR-VIEW: The Aviation Image Repository for Visibility Estimation of Weather, A Dataset and Benchmark
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Abstract (arXiv)
Machine Learning for aviation weather is a growing area of research for providing low-cost alternatives for traditional, expensive weather sensors; however, in the area of atmospheric visibility estimation, publicly available datasets, tagged with visibility estimates, of distances relevant for aviation, of diverse locations, of sufficient size for use in supervised learning, are absent. This paper introduces a new dataset which represents the culmination of a year-long data collection campaign of images from the FAA weather camera network suitable for this purpose. We also present a benchmark when applying three commonly used approaches and a general-purpose baseline when trained and tested on three publicly available datasets, in addition to our own, when compared against a recently ratified ASTM standard.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 4 of its 28 references that are in the map. First posted on arXiv 26 Jun 2025.
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4 of 28 references.
References · 4
- 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
- 2017Semantic Foggy Scene Understanding with Synthetic Datacited by 401
- 2019Gated2Depth: Real-time Dense Lidar from Gated Imagescited by 23
- 2024SynFog: A Photo-realistic Synthetic Fog Dataset based on End-to-end Imaging Simulation for Advancing Real-World Defogging in Autonomous Drivingcited by 9
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