Symmetric Triangle Network for Object Detection Within X-ray Baggage Security Imagery

X-ray baggage security image inspection is crucial for maintaining safety and is difficult due to the 2D projection nature of the images and variable sizes of objects. We proposed an anchor-free symmetric triangle network (ST-Net) for object detection within X-ray baggage security imagery. The ST-Net has three main components: bottom-up structure, Symmetric triangle feature pyramid module (STFPM) and detector head. Specifically, the STFPM module has multiple paths with different directions and lengths, which can fuse the rich multi-scale feature representation. Symmetry structure can effectively supplement the global feature information. In addition, we built a new dualenergy (DE) dataset generated from the real dual-energy images to preserve the original information. Experiments on DE dataset and public SIXray dataset demonstrate the proposed ST-Net could surpass most existing methods.