RoadAnomaly21
收藏arXiv2025-09-30 收录
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资源简介：
该数据集包含了真实道路驾驶场景中的非分布对象。此外，该数据集还使用了如AUPR（面积下精准率）和FPR（错误正类率）等与阈值无关的指标进行评估。其任务是对非分布对象进行无监督检测。
This dataset contains out-of-distribution (OOD) objects in real road driving scenarios. Additionally, threshold-independent metrics such as AUPR (Area Under the Precision-Recall Curve) and FPR (False Positive Rate) are employed for evaluation, and its core task is unsupervised detection of out-of-distribution objects.
提供机构：
SegmentMeIfYouCan (SMIYC) benchmark
