Jihoon Hong, Alireza Kheirandish, Rohan Sanda, Sara Fridovich-Keil · 2026 · arXiv
DOI: 10.48550/arXiv.2610.31538 · open-access PDF
局部异常检测是识别空间限制的异常或分布外(OOD)区域的任务,在另一种分布内(ID)图像中。大多数现有的方法是专为特定背景而设计的,重点是工业缺陷检测,在那里它们在已确立的基准上实现了卓越的性能。
Machine translation (Meta M2M100); the English original follows.
Local anomaly detection is the task of identifying spatially confined anomalous or out-of-distribution (OOD) regions within an otherwise in-distribution (ID) image. Most existing methods are designed for a specific context, with a strong focus on industrial defect detection, where they achieve excellent performance on well-established benchmarks. However, we observe that these methods can exhibit significant performance drops in other contexts, especially when the inlier distribution is multimodal. To account for this inlier complexity, we propose LACToS, a principled local OOD detection metho
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