Dataset | Year | Classes | Images | Annotations | Type | Scene | Application | Availability | |||
Total | Prohibited | Image | Bbox | Mask | |||||||
GDXray[5] Dbf6 Dbf3 Liu et al. SIXray[4] OPIXray[1] HiXray[2] PIDray[3] | 2015 2017 2018 2019 2019 2020 2021 2021 | 3 6 3 6 6 5 8 12 | 8150 11627 7603 32253 1059231 8885 45364 47677 | 8150 11627 7603 12683 8929 8885 45364 47677 | √ √ √ √ √ √ √ √ | √ √ √ √ √ √ √ √ | √ | Real Real Real Real Real Synthetic Real Real | - - - S S A A S + A + R | C + O C + O C + O C + O C + O C + O C + O C + O + I | √ √ √ √ √ |
【2022】
Towards Automatic Threat Detection: A Survey of Advances of Deep Learning within X-ray Security Imaging:PR,2022【原文】
[ 1 ] ^{[1]} [1]Occluded Prohibited Items Detection: an X-ray Security Inspection Benchmark and De-occlusion Attention Module:ACM MM,2020 【原文】
Towards More Efficient Security Inspection via Deep Learning: A Task-Driven X-ray Image Cropping Scheme:Micromachines (Basel),2022【原文】
EAOD-Net: Effective anomaly object detection networks for X-ray images:IET Image Processing,2022【原文】
A Lightweight Dangerous Liquid Detection Method Based on Depthwise Separable Convolution for X-Ray Security Inspection:Computational Intelligence and Neuroscience,2022【原文】
【2021】
Operationalizing Convolutional Neural Network Architectures for Prohibited Object Detection in X-Ray Imagery:ICMLA,2021【原文】
A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband Items:TSMC,2021【原文】
[ 2 ] ^{[2]} [2]Towards Real-world X-ray Security Inspection: A High-Quality Benchmark And Lateral Inhibition Module For Prohibited Items Detection:ICCV,2021 【原文】
[ 3 ] ^{[3]} [3]Towards Real-World Prohibited Item Detection: A Large-Scale X-ray Benchmark:ICCV,2021 【原文】【翻译】
An automated detection model of threat objects for X-ray baggage inspection based on depthwise separable convolution:J Real-Time Image Proc,2021【原文】
Benign Object Detection and Distractor Removal in 2D Baggage Scans:PRIP, TU Wien,2021【原文】
On the Impact of Using X-Ray Energy Response Imagery for Object Detection Via Convolutional Neural Networks:ICIP,2021【原文】
Pixel-Level Analysis for Enhancing Threat Detection in Large-Scale X-ray Security Images :Applied Sciences,2021 【原文】
Unsupervised anomaly instance segmentation for baggage threat recognition:J Ambient Intell Human Comput,2021【原文】
Over-sampling De-occlusion Attention Network for Prohibited Items Detection in Noisy X-ray Images :arXiv:2103.00809,2021【原文】
【2020】
A novel enhanced region proposal network and modified loss function : Threat object detection in secure screening using deep learning:Journal of Supercomputing,2020【原文】
Data Augmentation of X-Ray Images in Baggage Inspection Based on Generative Adversarial Networks:IEEE Access,2020【原文】
Cascaded Structure Tensor Framework for Robust Identification of Heavily Occluded Baggage Items from X-ray Scans: arXiv:2004.06780,2020【原文】
【2019】
YOLO-based Threat Object Detection in X-ray Images:HNICEM,2019【原文】
Evaluation of a Dual Convolutional Neural Network Architecture for Object-wise Anomaly Detection in Cluttered X-ray Security Imagery:ICMLA,2019【原文】
On the Impact of Object and Sub-component Level Segmentation Strategies for Supervised Anomaly Detection within X-ray Security Imagery: ICMLA,2019【原文】
Evaluating the Transferability and Adversarial Discrimination of Convolutional Neural Networks for Threat Object Detection and Classification within X-Ray Security Imagery:ICMLA,2019【原文】
[ 4 ] ^{[4]} [4]SIXray: A Large-Scale Security Inspection X-Ray Benchmark for Prohibited Item Discovery in Overlapping Images:CVPR,2019【原文】
Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection:IJCNN,2019【原文】
KNN-Based Automatic Cropping for Improved Threat Object Recognition in X-Ray Security Images:Journal of IKEEE,2019 【原文】
Toward Automatic Threat Recognition for Airport X-ray Baggage Screening with Deep Convolutional Object Detection : arXiv:1912.06329,2019【原文】
【2018】
“Unexpected Item in the Bagging Area”: Anomaly Detection in X-Ray Security Images:TIFS,2018【原文】
Multi-view X-Ray R-CNN:GCPR,2018 【原文】
GANomaly: Semi-supervised Anomaly Detection via Adversarial Training:ACCV,2018【原文】
【2017】
An evaluation of region based object detection strategies within X-ray baggage security imagery:ICIP,2017【原文】
【2015】
[ 5 ] ^{[5]} [5]GDXray: The Database of X-ray Images for Nondestructive Testing:Journal of Nondestructive Evaluation,2015【原文】