EdgeZSAD: Practical Zero-Shot Anomaly Detection on Edge Devices
Industrial inspection needs zero-shot anomaly detection (ZSAD) that remains useful under edge deployment constraints. Recent methods often rely on ViT-L foundation backbones (~300M parameters), which exceed the memory and operator budget of typical embedded hardware. We study this regime through EdgeZSAD, a compact reference system built around a TinyViT-21M-512 backbone, an asymmetric global-local readout (EdgeGLR), and a reproducible source-side training recipe (Real-IAD-DR). We train a single checkpoint in a source-trained, target-unseen protocol and evaluate it across six industrial benchmarks. Across three independent runs, the resulting model reaches an average image AUROC of 91.6 o...
| Authors | Taewan Cho, Andrew Jaeyong Choi |
|---|---|
| Primary category | cs.CV |
| Published | 15 June 2026 |
| Last updated at source | 15 June 2026 |
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