Datasets › HAC

HAC (Hybrid Adverse Conditions)

Introduced by Ye-Cong Wan et al. in Restoring Images Captured in Arbitrary Hybrid Adverse Weather Conditions in One Go17 May 2023 archive 2025-07-28

HAC is a dataset for learning and benchmarking arbitrary Hybrid Adverse Conditions restoration. HAC contains 31 scenarios composed of an arbitrary combination of five common weather, with a total of 316K adverse-weather/clean pairs.

Source: Restoring Images Captured in Arbitrary Hybrid Adverse Weather Conditions in One Go

Image Source: Restoring Images Captured in Arbitrary Hybrid Adverse Weather Conditions in One Go

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • HAC

1 variant name, as the archive lists them.

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