Author

Jhih-Ciang Wu

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Preprint Aug 2026

GeoMAD: Geometry-Aware Multi-View Anomaly Detection via Deformable Fusion and Distributional Alignment

Multi-view anomaly detection (MvAD) detects defects by exploiting complementary observations from multiple camera viewpoints. The central challenge is to fuse views with sufficient geometric awareness while remaining scalable to multi-class industrial settings. Existing methods typically fall into two extremes: voxel-b...

Shang-Fu Chen, Jhih-Ciang Wu, Kuan-Chuan Peng et al. · 0 citations

Preprint Aug 2026

NFAD: Nuisance-Filtered Anomaly Detection Under Distribution Shift

Recent advances in anomaly detection (AD) for industrial inspection have pushed performance on standard benchmarks toward saturation. However, strong benchmark performance does not necessarily translate to real-world deployment, as these benchmarks are primarily collected under controlled acquisition conditions. Change...

Dat Cao, Son T. Nghiem, Phan Nguyen et al. · 0 citations