Detecting Overlapping Objects in X-ray Security Imagery by a Label-aware Mechanism
One of the key challenges to the X-ray security check is to detect the overlapped items in backpacks or suitcases in the X-ray images. Most existing methods improve the robustness of models to the object overlapping problem by enhancing the underlying visual information such as colors and edges. However, this strategy ignores the situations in which the objects have similar visual clues as to the background, and objects overlapping each other. Since the two cases rarely appear in existing datasets, we contribute a novel dataset – Cutters and Liquid Containers X-ray Dataset (CLCXray) to complete the related research.
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| Task | Dataset | Model | Metric Name | Metric Value | Global Rank | Benchmark |
|---|---|---|---|---|---|---|
| 2D Object Detection | CLCXray | LACLS | Detection: Full (mAP@0.5) | 59.3 | # 1 |
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