counterfactual-training

The paper introduces Chimera Training, a method for logical anomaly detection that uses counterfactual construction at the feature level to train neural rule evaluators without requiring real anomalous images, improving rule-level anomaly detection performance on benchmarks like CLEVRER, OpenImages, and VidOR.