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AllClear: A Comprehensive Dataset and Benchmark for Cloud Removal in Satellite Imagery
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Introduces AllClear, a large public multi-temporal dataset of 23,742 globally distributed ROIs with diverse land-use for cloud removal in satellite imagery, plus a benchmark for evaluating cloud removal methods.
Problem
Cloud removal in satellite imagery lacks a comprehensive benchmark and a sufficiently large, diverse training dataset.
Approach
A large, globally distributed multi-temporal satellite dataset with diverse land use and cloud conditions, paired with a benchmark for training and evaluating cloud removal models. The provided text is only the NeurIPS template and abstract fragment, so most method and result details are not available.
Key results
- Dataset comprises 23,742 globally distributed ROIs with diverse land-use (per abstract).
Experimental setup
Benchmarks: AllClear benchmark
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