Abstract
Existing 3D industrial anomaly detection mainly targets local geometric deviations. In contrast, many industrial anomalies violate object-level design or assembly rules, which we define as 3D logical anomalies. To address these challenges, we introduce the Industrial Logical Anomaly Detection Dataset (ILGAD), the first scalable benchmark dedicated to logical anomalies in industrial point clouds. ILGAD contains 2,774 samples from 15 categories with point-level annotations and covers existence, specification, pose, and assembly-state errors. To detect such 3D logical anomalies, we propose a consistency reasoning framework that assesses whether local geometry, structure coverage, and spatial relations conform to the normal design. The framework detects geometric changes, unsupported expected structures, and abnormal local arrangements. Experiments on ILGAD, Anomaly-ShapeNet, and IEC3D demonstrate superior object-level detection and point-level localization, showing that the framework effectively detects logical anomalies and generalizes to conventional geometric defects.
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Publication details
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Cite this article
APA 7
Qin, Z., Xie, H., Yi, J., Yang, Y., Wang, H., Cao, Y., Zhang, H., & Wang, Y. (2026). Beyond Geometry: Benchmarking and Consistency Reasoning for 3D Logical Anomaly Detection. https://omanscience.com/en/articles/beyond-geometry-benchmarking-and-consistency-reasoning-for-3d-logical-anomaly-detection
MLA 9
Qin, Zhiqiang, et al. "Beyond Geometry: Benchmarking and Consistency Reasoning for 3D Logical Anomaly Detection." https://omanscience.com/en/articles/beyond-geometry-benchmarking-and-consistency-reasoning-for-3d-logical-anomaly-detection.
Chicago (author–date)
Qin, Zhiqiang, He Xie, Junfei Yi, Yang Yang, Hao Wang, Yunkang Cao, Hui Zhang, and Yaonan Wang. 2026. "Beyond Geometry: Benchmarking and Consistency Reasoning for 3D Logical Anomaly Detection." https://omanscience.com/en/articles/beyond-geometry-benchmarking-and-consistency-reasoning-for-3d-logical-anomaly-detection.
Harvard
Qin, Z., Xie, H., Yi, J., Yang, Y., Wang, H., Cao, Y., Zhang, H. and Wang, Y. (2026) 'Beyond Geometry: Benchmarking and Consistency Reasoning for 3D Logical Anomaly Detection', Available at: https://omanscience.com/en/articles/beyond-geometry-benchmarking-and-consistency-reasoning-for-3d-logical-anomaly-detection.
Vancouver
Qin Z, Xie H, Yi J, Yang Y, Wang H, Cao Y, et al. Beyond Geometry: Benchmarking and Consistency Reasoning for 3D Logical Anomaly Detection. https://omanscience.com/en/articles/beyond-geometry-benchmarking-and-consistency-reasoning-for-3d-logical-anomaly-detection
IEEE
Z. Qin, H. Xie, J. Yi, Y. Yang, H. Wang, Y. Cao, H. Zhang, and Y. Wang, "Beyond Geometry: Benchmarking and Consistency Reasoning for 3D Logical Anomaly Detection," https://omanscience.com/en/articles/beyond-geometry-benchmarking-and-consistency-reasoning-for-3d-logical-anomaly-detection.