ACDC (Adverse Conditions Dataset with Correspondences) (Adverse Conditions Dataset with Correspondences)

We introduce ACDC, the Adverse Conditions Dataset with Correspondences for training and testing semantic segmentation methods on adverse visual conditions. It comprises a large set of 4006 images which are evenly distributed between fog, nighttime, rain, and snow. Each adverse-condition image comes with a high-quality fine pixel-level semantic annotation, a corresponding image of the same scene taken under normal conditions and a binary mask that distinguishes between intra-image regions of clear and uncertain semantic content.

ACDC supports two tasks: 1. standard semantic segmentation 2. uncertainty-aware semantic segmentation


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