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SegmentMeIfYouCan - A Benchmark for Anomaly Segmentation
The detection and localization of previously-unseen objects is of utmost importance for safety-critical applications such as perception for automated driving, especially if such unknown objects appear on the road ahead. Our benchmark addresses two tasks: Anomalous object segmentation, which considers any previously-unseen object category; and road obstacle segmentation, which focuses on any object on the road, may it be known or unknown. We provide two corresponding datasets together with a test suite, performing an in-depth method analysis.