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RAD: A Dataset and Benchmark for Real-Life Anomaly Detection with Robotic Observations
Anomaly detection is essential for robotic perception and industrial inspection, yet most benchmarks are collected under controlled conditions with fixed viewpoints and stable illumination. These settings do not reflect robotic deployment, where camera pose, lighting, and surface reflectance vary co
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