RoadAnomaly21 is a dataset for anomaly segmentation, the task of identify the image regions containing objects that have never been seen during training. It consists of an evaluation dataset of 100 images with pixel-level annotations. Each image contains at least one anomalous object, e.g. animals or unknown vehicles. The anomalies can appear anywhere in the image and widely differ in size, covering from 0.5% to 40% of the image
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