Localisation-Aware Uncertainty for Pretrained Object Detection

Summary

The paper introduces GRACE, a lightweight post-hoc evidential meta-model that estimates per-bounding-box localisation uncertainty in pretrained object detectors while the base detector stays frozen. It builds a curriculum via saliency-guided modification and combines localisation error, modification level, and prediction instability as training targets. Across adversarial attacks and evaluated strengths, GRACE improves TP-FP AUROC by 22% relative to the strongest comparator in some cases while maintaining in-distribution detection performance.

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