CAVE: Detecting and Explaining Commonsense Anomalies in Visual Environments

arXiv — cs.CV•Friday, October 31, 2025 at 4:00:00 AM

The introduction of CAVE marks a significant advancement in the field of computer vision by providing a benchmark for detecting and explaining real-world visual anomalies. Unlike previous methods that focused on industrial defects or synthetic anomalies, CAVE captures the complexity and unpredictability of real-life situations. This development is crucial as it enhances the ability of machines to understand and interact with their environments more effectively, paving the way for improved applications in various sectors such as robotics and surveillance.

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