SIXray: A Large-Scale Security Inspection X-Ray Benchmark for Prohibited Item Discovery in Overlapping Images

By Caijing Miao, Lingxi Xie, Fang Wan, Chi Su, Hongye Liu, Jianbin Jiao, Qixiang Ye. 2019

316 citations recorded by the source corpus.

In this paper, we present a large-scale dataset and establish a baseline for prohibited item discovery in Security Inspection X-ray images. Our dataset, named SIXray, consists of 1,059,231 X-ray images, in which 6 classes of 8,929 prohibited items are manually annotated. It raises a brand new challenge of overlapping image data, meanwhile shares the same properties with existing datasets, including complex yet meaningless contexts and class imbalance. We propose an approach named class-balanced hierarchical refinement (CHR) to deal with these difficulties. CHR assumes that each input image is sampled from a mixture distribution, and that deep networks require an iterative process to infer image contents accurately. To accelerate, we insert reversed connections to different network backbones, delivering high-level visual cues to assist mid-level features. In addition, a class-balanced loss function is designed to maximally alleviate the noise introduced by easy negative samples. We evaluate CHR on SIXray with different ratios of positive/negative samples. Compared to the baselines, CHR enjoys a better ability of discriminating objects especially using mid-level features, which offers the possibility of using a weakly-supervised approach towards accurate object localization. In particular, the advantage of CHR is more significant in the scenarios with fewer positive training samples, which demonstrates its potential application in real-world security inspection.

Subfields: Artificial Intelligence, Biomedical Engineering, Computer Vision and Pattern Recognition, Evaluation & Benchmarks, Privacy & Security

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Yanlu Wei
2. Libo Zhang
3. Jay Zhangjie Wu
4. Longyin Wen
5. Yuqing Ma
6. Xianglong Liu
7. Yanjun Wu

In Biomedical Engineering

1. Longyin Wen

In Computer Vision and Pattern Recognition

1. Renshuai Tao
2. Yanlu Wei
3. Libo Zhang
4. Boying Wang
5. Jay Zhangjie Wu
6. Longyin Wen
7. Yuqing Ma
8. Xianglong Liu

In Evaluation & Benchmarks

1. Longyin Wen
2. Xianglong Liu

Citations in the corpus

• Towards Real-World Prohibited Item Detection: A Large-Scale X-ray Benchmark (2021, background): “To advance the developments of prohibited items detection in X-ray images, some recent attempts devote to construct security inspection benchmarks [25, 1, 2, 26, 36].”
• Occluded Prohibited Items Detection: An X-ray Security Inspection Benchmark and De-occlusion Attention Module (2020, methodology): “X-ray offers powerful ability in many tasks such as medical imaging analysis [1, 9, 16] and security inspection [11, 18].”