AnomalousPatchCore：探索异常样本在工业异常检测中的应用
AnomalousPatchCore: Exploring the Use of Anomalous Samples in Industrial Anomaly Detection
AI总结：
提出AnomalousPatchCore (APC)异常检测系统，利用正常和异常的领域内样本微调特征提取器并构建记忆库，通过三个辅助任务解决分类与定位及样本不平衡问题，在MVTec数据集上优于现有方法。
摘要：
视觉检查，即工业异常检测，是制造业中最常见的质量控制类型之一。该任务旨在给定图像的情况下识别是否存在异常，例如电路板图像上缺失的组件，以便后续进行人工检查。尽管近年来工业异常检测取得了显著进展，但大多数异常检测方法仍然仅利用正常样本的知识，未能利用经常可用的异常样本中的信息。此外，它们严重依赖于在常见图像分类数据集上预训练的非常通用的特征提取器。在本文中，我们解决了这些不足，提出了新的异常检测系统AnomalousPatchCore (APC)，该系统基于使用正常和异常的领域内样本微调的特征提取器，以及随后用于识别异常特征的记忆库。为了微调APC中的特征提取器，我们提出了三个辅助任务，这些任务解决了异常检测的不同方面（分类与定位），并减轻了正常和异常样本之间不平衡的影响。我们在MVTec数据集上的广泛评估表明，APC在检测异常方面优于最先进的系统，鉴于后续的人工检查，这在工业异常检测中尤为重要。在详细的消融研究中，我们进一步调查了APC的特性。
英文摘要：
Visual inspection, or industrial anomaly detection, is one of the most common quality control types in manufacturing. The task is to identify the presence of an anomaly given an image, e.g., a missing component on an image of a circuit board, for subsequent manual inspection. While industrial anomaly detection has seen a surge in recent years, most anomaly detection methods still utilize knowledge only from normal samples, failing to leverage the information from the frequently available anomalous samples. Additionally, they heavily rely on very general feature extractors pre-trained on common image classification datasets. In this paper, we address these shortcomings and propose the new anomaly detection system AnomalousPatchCore~(APC) based on a feature extractor fine-tuned with normal and anomalous in-domain samples and a subsequent memory bank for identifying unusual features. To fine-tune the feature extractor in APC, we propose three auxiliary tasks that address the different aspects of anomaly detection~(classification vs. localization) and mitigate the effect of the imbalance between normal and anomalous samples. Our extensive evaluation on the MVTec dataset shows that APC outperforms state-of-the-art systems in detecting anomalies, which is especially important in industrial anomaly detection given the subsequent manual inspection. In detailed ablation studies, we further investigate the properties of our APC.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
