Confidence-feedback-weighted graph matching network: online-offline laser-induced damage site matching under complex interference
Online inspection images of final optics in high-power laser facilities contain pseudo-damage sites that closely resemble true damage sites. Determining the authenticity of online-detected sites is therefore difficult and requires accurate matching to offline ground-truth sites. However, this matching remains highly challenging due to limited match-discriminative features, local geometric distortions, and numerous distractor sites. Existing matching models mainly suppress distractors implicitly through loss-function supervision. We propose a confidence-feedback-weighted graph matching network that requires only damage-site centroid coordinates as input. It estimates node matchability conf...
| Authors | Yueyue Han, Guanhua Chen, Hangcheng Dong et al. |
|---|---|
| Primary category | cs.CV |
| Published | 28 June 2026 |
| Last updated at source | 28 June 2026 |
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