We propose a novel method for Zero-Shot Anomaly Localization that leverages a bidirectional mapping derived from the 1-dimensional Wasserstein Distance. The proposed approach allows pinpointing the anomalous regions in a texture with increased precision by aggregating the contribution of a pixel to the errors of all nearby patches. We validate our solution on several datasets and obtain more than a 40% reduction in error over the previous state of the art on the MVTec AD dataset in a zero-shot setting.
翻译:我们提出了一种新的零样本异常定位方法,利用从1维 Wasserstein 距离派生的双向映射。所提出的方法通过聚合一个像素对所有附近补丁的错误的贡献,从而可以更精确地定位纹理中的异常区域。我们在多个数据集上验证了我们的解决方案,在零样本设置下,相对於MVTec AD数据集上的之前的最新技术,我们实现了超过40%的误差降低。