Security inspectors struggle to accurately detect the prohibited items in daily security inspection, which may cause severe danger to the public. Therefore, it is vital to develop a rapid, accurate and automatic detection model using powerful deep learning method. 

To accelerate the research on enhancing horizontal object detection performance in the X-ray scenario, we organize this challenge track, where image data in real X-ray security inspection scene with horizontal bounding boxes are provided .

Horizontal bounding boxes are incapable of representing slender prohibited items in various orientations, which involve in massive background information. Therefore exploring rotated object detection task on X-ray security inspection scenario is significant. 

To accelerate the research on enhancing rotated object detection performance in the X-ray scenario, we organize this challenge track, where image data in real X-ray security inspection scene with rotated bounding boxes are provided .