# xray **Repository Path**: warriorschampion/xray ## Basic Information - **Project Name**: xray - **Description**: No description available - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2026-09-14 - **Last Updated**: 2026-09-14 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README

**XrayVision: Brief history of X-ray security imaging in Computer Vision** ---

:boom: List of datasets and papers (not exhaustive)! :owl: * Our epochal mission: Time to gather all those papers and datasets about X-ray security imaging onto this page! Let's turn this into the one-stop-shop for the research community - no need to wander around - we've got you covered! * :space_invader: This is constantly updated with the latest datasets, papers - check in regularly for updates!

## :dragon_face: Dataset :chart_with_upwards_trend: [2D: 18] [3D: 2] |Name | Type | Year | Class |Prohibited - Negative| Annotations| Views|Open Source | |-----------|------|------|-------------|-------------|------|-----|------| |LDXray |2D | 2024 |12 |146,997 - 0 | bbox| 2 |✕ [[Link]](https://arxiv.org/abs/2411.18082) | |DVXRAY |2D | 2024 |15 |10,000 - 22,0000 | bbox| 2 |✓ [[Link]](https://ieeexplore.ieee.org/document/10458082) | |LPIXray |2D | 2023 |18 |60,950 - 0 | bbox|1 |✕ [[Link]](https://ieeexplore.ieee.org/document/10350273) | |FSOD |2D | 2022 |20 |12,333 - 0 | bbox|1 |✓ [[Link]](https://github.com/DIG-Beihang/XrayDetection) | |EDS |2D | 2022 |10 |14,219 - 0 | bbox|1 |✓ [[Link]](https://github.com/DIG-Beihang/XrayDetection) | |Xray-PI |2D | 2022 |12 |2,409 - 0 | bbox, segm|1 |✓ [[Link]](https://github.com/LPAIS/Xray-PI) | |PIXray |2D | 2022 |12 |5,046 - 0 | bbox, segm|1 |✓ [[Link]](https://github.com/Mbwslib/DDoAS) | |CLCXray |2D | 2022 |12 |9,565 - 0 | bbox|1 |✓ [[Link]](https://github.com/GreysonPhoenix/CLCXray) | |HiXray |2D | 2021 |8 |45,364 - 0 | bbox|1 |✓ [[Link]](https://github.com/DIG-Beihang/XrayDetection) | |deei6 |2D | 2021 |6 |7,022 - 0 | bbox, segm|2 |✕ [[Link]](https://breckon.org/toby/publications/papers/bhowmik21energy.pdf) | |PIDray |2D | 2021 |12 |47,677 - 0 | bbox, segm|1 |✓ [[Link]](https://github.com/bywang2018/security-dataset) | |AB |2D | 2021 |-- |417 - 6,608 | -- |2 |✕ [[Link]](https://ieeexplore.ieee.org/document/9534034) | |dbf4 |2D | 2020 |4 |10,112 - 0 | bbox, segm|4 |✕ [[Link]](https://breckon.org/toby/publications/papers/isaac20multiview.pdf) | |OPIXray |2D | 2020 |5 |8,885 - 0 | bbox |1 |✓ [[Link]](https://github.com/OPIXray-author/OPIXray) | |SIXray |2D | 2019 |6 |8,929 - 1,050,0302 | bbox |1 |✓ [[Link]](https://github.com/MeioJane/SIXray) | |COMPASS-XP |2D | 2019 |366 |1928 - 0 | -- |1 |✓ [[Link]](https://zenodo.org/record/2654887#.YUtGVHVKikA) | |dbf6 |2D | 2018 |6 |11,627 - 0 | bbox, segm|4 |✕ [[Link]](https://breckon.org/toby/publications/papers/akcay18architectures.pdf) | |GDXray |2D | 2015 |5 |19,407 - 0 | bbox |1 |✓ [[Link]](https://domingomery.ing.puc.cl/material/gdxray/) | |Dur_3D |3D | 2020 |5 |774 - 0 | bbox | -- |✕ [[Link]](https://arxiv.org/abs/2008.01218) | |Flitton_3D |3D | 2015 |2 |810 - 2149 | bbox | -- |✕ [[Link]](https://breckon.org/toby/publications/papers/flitton15codebooks.pdf) | --- ## :scroll: Paper :chart_with_upwards_trend: [2D: 168] [3D: 38] :ant: [[Dataset]](#dragon_face-dataset) [[2024]](#2024) [[2023]](#2023) [[2022]](#2022) [[2021]](#2021) [[2020]](#2020) [[2019]](#2019) [[2018]](#2018) [[Earlier]](#earlier) [[Reference]](#frog-reference) ### 2024 [^[top]](#scroll-paper) #### 2D - BGM: Background Mixup for X-ray Prohibited Items Detection [[Paper]](https://arxiv.org/abs/2412.00460) - Dual-view X-ray Detection: Can AI Detect Prohibited Items from Dual-view X-ray Images like Humans? [[Paper]](https://arxiv.org/abs/2411.18082) - MMCL: Boosting Deformable DETR-Based Detectors with Multi-Class Min-Margin Contrastive Learning for Superior Prohibited Item Detection [[Paper]](https://arxiv.org/abs/2406.03176) - Self-Supervised Anomaly Detection and a New Benchmark for X-Ray Cargo Images [[Paper]](https://ieeexplore.ieee.org/abstract/document/10648123) - CLIFS: Clip-Driven Few-Shot Learning for Baggage Threat Classification [[Paper]](https://ieeexplore.ieee.org/document/10647879) - Adaptxray: Vision Transformer And Adapter In X-Ray Images For Prohibited Items Detection [[Paper]](https://ieeexplore.ieee.org/document/10648133) - Performance Evaluation of Segment Anything Model with Variational Prompting for Application to Non-Visible Spectrum Imagery [[Paper]](https://arxiv.org/abs/2404.12285) - An Optimized Mask R-CNN with Bag-of-Visual Words and Fast+Surf Algorithm in Sharp Object Instance Segmentation for X-ray Security [[Paper]](https://www.temjournal.com/content/132/TEMJournalMay2024_926_939.html) - Multi-Scale Hierarchical Contour Framework for Detecting Cluttered Threats in Baggage Security [[Paper]](https://ieeexplore.ieee.org/document/10542724) - Towards Dual-view X-ray Baggage Inspection: A Large-scale Benchmark and Adaptive Hierarchical Cross Refinement for Prohibited Item Discovery [[Paper]](https://ieeexplore.ieee.org/document/10458082) - X-ray image analysis for explosive circuit detection using deep learning algorithms [[Paper]](https://www.sciencedirect.com/science/article/abs/pii/S1568494623011511?via%3Dihub) ### 2023 [^[top]](#scroll-paper) #### 2D - Unaligned 2D to 3D Translation with Conditional Vector-Quantized Code Diffusion using Transformers [[Paper]](https://openaccess.thecvf.com/content/ICCV2023/html/Corona-Figueroa_Unaligned_2D_to_3D_Translation_with_Conditional_Vector-Quantized_Code_Diffusion_ICCV_2023_paper.html) - Enhanced detonators detection in X-ray baggage inspection by image manipulation and deep convolutional neural networks [[Paper]](https://www.nature.com/articles/s41598-023-41651-y) - Illicit item detection in X-ray images for security applications [[Paper]](https://ieeexplore.ieee.org/document/10233969) - Enhancing baggage inspection through computer vision analysis of x-ray images [[Paper]](https://link.springer.com/article/10.1007/s12198-023-00270-4) - GADet: A Geometry-Aware X-ray Prohibited Items Detector [[Paper]](https://ieeexplore.ieee.org/document/10322651) - LPIXray: A Large-scale Logistics Prohibited Item X-ray Dataset for the Application of Deep Learning in Security Inspection [[Paper]](https://ieeexplore.ieee.org/document/10350273) - Electronic explosives inspection: a fine-grained X-ray benchmark and few-shot prohibited phone detection model [[Paper]](https://link.springer.com/article/10.1007/s11042-023-17388-1) - DETR Based Prohibited Item Detection in X-ray Security Checking Images [[Paper]](https://ieeexplore.ieee.org/document/10260512) - Feature-Aware Prohibited Items Detection for X-Ray Image [[Paper]](https://ieeexplore.ieee.org/document/10223152) - A literature review on deep learning algorithms for analysis of X-ray images [[Paper]](https://link.springer.com/article/10.1007/s13042-023-01961-z) - X-ray Detection of Prohibited Item Method Based on Dual Attention Mechanism [[Paper]](https://www.mdpi.com/2079-9292/12/18/3934) - Inspection of cargo using dual-energy X-ray radiography: A review [[Paper]](https://www.sciencedirect.com/science/article/abs/pii/S0969806X23004255?via%3Dihub#cebib0010) - Programmable broad learning system for baggage threat recognition [[Paper]](https://link.springer.com/article/10.1007/s11042-023-16057-7) - SLX: Similarity Learning for X-Ray Screening and Robust Automated Disassembled Object Detection [[Paper]](https://ieeexplore.ieee.org/document/10190997) - Attention Based Network with DA-Loss for X-ray Contraband Automatic Detection [[Paper]](https://ieeexplore.ieee.org/document/10219712) - AC-YOLOv4: an object detection model incorporating attention mechanism and atrous convolution for contraband detection in x-ray images [[Paper]](https://link.springer.com/article/10.1007/s11042-023-16628-8) - FSVM: A Few-Shot Threat Detection Method for X-ray Security Images [[Paper]](https://www.mdpi.com/1424-8220/23/8/4069) - Incremental Instance Segmentation for Cluttered Baggage Threat Detection [[Paper]](https://ieeexplore.ieee.org/document/10231011) - Optimization and Research of Suspicious Object Detection Algorithm in X-ray Image [[Paper]](https://ieeexplore.ieee.org/document/10082660) - Object Detection and X-Ray Security Imaging: A Survey [[Paper]](https://ieeexplore.ieee.org/abstract/document/10120944) - RWSC-Fusion: Region-Wise Style-Controlled Fusion Network for the Prohibited X-Ray Security Image Synthesis [[Paper]](https://openaccess.thecvf.com/content/CVPR2023/html/Duan_RWSC-Fusion_Region-Wise_Style-Controlled_Fusion_Network_for_the_Prohibited_X-Ray_Security_CVPR_2023_paper.html) - Transformers for Imbalanced Baggage Threat Recognition [[Paper]](https://ieeexplore.ieee.org/document/9977427) - CTA-FPN: Channel-Target Attention Feature Pyramid Network for Prohibited Object Detection in X-ray Images [[Paper]](https://link.springer.com/article/10.1007/s11220-023-00416-7) - Material-Aware Path Aggregation Network and Shape Decoupled SIoU for X-ray Contraband Detection [[Paper]](https://www.mdpi.com/2079-9292/12/5/1179) - Seeing Through the Data: A Statistical Evaluation of Prohibited Item Detection Benchmark Datasets for X-ray Security Screening [[Paper]](https://breckon.org/toby/publications/papers/isaac23evaluation.pdf) - X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item Detection [[Paper]](https://arxiv.org/abs/2302.09491) - Cascaded structure tensor for robust baggage threat detection [[Paper]](https://link.springer.com/article/10.1007/s00521-023-08296-4) - Computer Vision on X-ray Data in Industrial Production and Security Applications: A Comprehensive Survey [[Paper]](https://ieeexplore.ieee.org/document/10005308) ### 2022 [^[top]](#scroll-paper) #### 2D - Learning-based Material Classiﬁcation in X-ray Security Images [[Paper]](https://www.scitepress.org/Papers/2020/89517/pdf/index.html) - Few-shot X-ray Prohibited Item Detection: A Benchmark and Weak-feature Enhancement Network [[Paper]](https://dl.acm.org/doi/abs/10.1145/3503161.3548075) - Balanced Affinity Loss for Highly Imbalanced Baggage Threat Contour-Driven Instance Segmentation [[Paper]](https://ieeexplore.ieee.org/document/9897490) - Joint Sub-component Level Segmentation and Classification for Anomaly Detection within Dual-Energy X-Ray Security Imagery [[Paper]](https://arxiv.org/abs/2210.16453) - Automatic Baggage Threat Detection Using Deep Attention Networks [[Paper]](https://link.springer.com/chapter/10.1007/978-3-030-95070-5_11) - A Multi-Task Semantic Segmentation Network for Threat Detection in X-Ray Security Images [[Paper]](https://ieeexplore.ieee.org/document/9897736) - Dualray: Dual-View X-ray Security Inspection Benchmark and Fusion Detection Framework [[Paper]](https://link.springer.com/chapter/10.1007/978-3-031-18916-6_57#Fig6) - MFA-net: Object detection for complex X-ray cargo and baggage security imagery [[Paper]](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0272961) - Baggage Threat Recognition Using Deep Low-Rank Broad Learning Detector [[Paper]](https://ieeexplore.ieee.org/document/9842976) - Exploring Endogenous Shift for Cross-domain Detection: A Large-scale Benchmark and Perturbation Suppression Network [[Paper]](https://openaccess.thecvf.com/content/CVPR2022/papers/Tao_Exploring_Endogenous_Shift_for_Cross-Domain_Detection_A_Large-Scale_Benchmark_and_CVPR_2022_paper.pdf) - Improved YOLOX detection algorithm for contraband in X-ray images [[Paper]](https://opg.optica.org/ao/abstract.cfm?uri=ao-61-21-6297) - LightRay: Lightweight network for prohibited items detection in X-ray images during security inspection [[Paper]](https://www.sciencedirect.com/science/article/pii/S0045790622005110?via%3Dihub) - Benefits of Decision Support Systems in Relation to Task Difficulty in Airport Security X-Ray Screening [[Paper]](https://www.tandfonline.com/doi/full/10.1080/10447318.2022.2107775) - Recent Advances in Baggage Threat Detection: A Comprehensive and Systematic Survey [[Paper]](https://dl.acm.org/doi/10.1145/3549932) - Automated Detection of Threat Materials in X -Ray Baggage Inspection System (XBIS) [[Paper]](https://ieeexplore.ieee.org/document/9795120) - Threat detection in x-ray baggage security imagery using convolutional neural networks [[Paper]](https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12104/121040H/Threat-detection-in-x-ray-baggage-security-imagery-using-convolutional/10.1117/12.2622373.short?SSO=1) - X-ray baggage screening and artificial intelligence (AI) [[Paper]](https://op.europa.eu/en/publication-detail/-/publication/b6e77043-ede4-11ec-a534-01aa75ed71a1/language-en) - Material-aware Cross-channel Interaction Attention (MCIA) for occluded prohibited item detection [[Paper]](https://link.springer.com/article/10.1007/s00371-022-02498-y) - A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband Items [[Paper]](https://arxiv.org/abs/2201.02560) - How Realistic Is Threat Image Projection for X-ray Baggage Screening? [[Paper]](https://www.mdpi.com/1424-8220/22/6/2220) - Cross-modal Image Synthesis within Dual-Energy X-ray Security Imagery [[Paper]](https://openaccess.thecvf.com/content/CVPR2022W/PBVS/papers/Isaac-Medina_Cross-Modal_Image_Synthesis_Within_Dual-Energy_X-Ray_Security_Imagery_CVPRW_2022_paper.pdf) - Recursive CNN Model to Detect Anomaly Detection in X-Ray Security Image [[Paper]](https://ieeexplore.ieee.org/abstract/document/9754033?casa_token=Z5JOZgYLA-cAAAAA:8mR-hC0nj2sRu23gI0uZwt0w4K_oHfKcXVnCk6PMWjzmv9YzGxmLGIjDWkdriyqegNf44JRPHZc) - Towards More Efficient Security Inspection via Deep Learning: A Task-Driven X-ray Image Cropping Scheme [[Paper]](https://www.mdpi.com/2072-666X/13/4/565) - DMA-Net: Dual multi-instance attention network for X-ray image classification [[Paper]](https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/ipr2.12560) - X-ray security check image recognition based on attention mechanism [[Paper]](https://iopscience.iop.org/article/10.1088/1742-6596/2216/1/012104/meta) - A Data Augmentation Method for Prohibited Item X-Ray Pseudocolor Images in X-Ray Security Inspection Based on Wasserstein Generative Adversarial Network and Spatial-and-Channel Attention Block [[Paper]](https://www.hindawi.com/journals/cin/2022/8172466/) - Enhanced threat detection in three dimensions: An image-matched comparison of computed tomography and dual-view X-ray baggage screening [[Paper]](https://www.sciencedirect.com/science/article/pii/S0003687022001570) - ETHSeg: An Amodel Instance Segmentation Network and a Real-world Dataset for X-Ray Waste Inspection [[Paper]](https://openaccess.thecvf.com/content/CVPR2022/papers/Qiu_ETHSeg_An_Amodel_Instance_Segmentation_Network_and_a_Real-World_Dataset_CVPR_2022_paper.pdf) - Anomaly object detection in x-ray images with Gabor convolution and bigger discriminative RoI pooling [[Paper]](https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12177/121770B/Anomaly-object-detection-in-x-ray-images-with-Gabor-convolution/10.1117/12.2625815.short) - Intelligent Detection of Dangerous Goods in Security Inspection Based on Cascade Cross Stage YOLOv3 Model [[Paper]](https://hrcak.srce.hr/en/275305) - A Lightweight Dangerous Liquid Detection Method Based on Depthwise Separable Convolution for X-Ray Security Inspection [[Paper]](https://www.hindawi.com/journals/cin/2022/5371350/) - EAOD-Net: Effective anomaly object detection networks for X-ray images [[Paper]](https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/ipr2.12514) - American National Standard for Evaluating the Image Quality of X-ray Computed Tomography (CT) Security-Screening Systems [[Paper]](https://ieeexplore.ieee.org/document/9812579) - Automated Segmentation of Prohibited Items in X-ray Baggage Images Using Dense De-overlap Attention Snake [[Paper]](https://ieeexplore.ieee.org/document/9772992) - Programmable Broad Learning System to Detect Concealed and Imbalanced Baggage Threats [[Paper]](https://ieeexplore.ieee.org/document/9787420) - Few-Shot Segmentation for Prohibited Items Inspection with Patch-based Self-Supervised Learning and Prototype Reverse Validation [[Paper]](https://ieeexplore.ieee.org/document/9779459) - Augmenting data with GANs for firearms detection in cargo x-ray images [[Paper]](https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12104/1210406/Augmenting-data-with-GANs-for-firearms-detection-in-cargo-x/10.1117/12.2618887.short?SSO=1) - Weight-guided dual-direction-fusion feature pyramid network for prohibited item detection in x-ray images [[Paper]](https://www.spiedigitallibrary.org/journals/journal-of-electronic-imaging/volume-31/issue-3/033032/Weight-guided-dual-direction-fusion-feature-pyramid-network-for-prohibited/10.1117/1.JEI.31.3.033032.short) - Handling occlusion in prohibited item detection from X-ray images [[Paper]](https://link.springer.com/article/10.1007/s00521-022-07578-7) - Exploiting foreground and background separation for prohibited item detection in overlapping X-Ray images [[Paper]](https://www.sciencedirect.com/science/article/pii/S0031320321004416?casa_token=YKXXjKmLbXUAAAAA:zISg01iB-CP49Ek1rlneL-HftSZnYiA69izOwObqUUM5WdDawLxiSdUePbXI0lq7KF72Wgphfw) - PMix: a method to improve the classification of X-ray prohibited items based on probability mixing [[Paper]](https://www.inderscienceonline.com/doi/pdf/10.1504/IJWMC.2022.123318) - Detecting prohibited objects with physical size constraint from cluttered X-ray baggage images [[Paper]](https://www.sciencedirect.com/science/article/pii/S0950705121010686?casa_token=Y9V5DLzSMw0AAAAA:xyzOIGXtGxAPRaORWuiXWa0E7u2ICS4B1wcZvotPTI9wXzPFEp3IzDuhXKPubRsWX3Mu8q-4AA) - Synthetic threat injection using digital twin informed augmentation [[Paper]](https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12104/1210407/Synthetic-threat-injection-using-digital-twin-informed-augmentation/10.1117/12.2618972.short) - Target Detection by Target Simulation in X-ray Testing [[Paper]](https://link.springer.com/article/10.1007/s10921-022-00851-8) - Abnormal object detection in x-ray images with self-normalizing channel attention and efficient data augmentation [[Paper]](https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12177/121770M/Abnormal-object-detection-in-x-ray-images-with-self-normalizing/10.1117/12.2625843.short) - Raw data processing techniques for material classification of objects in dual energy X-ray baggage inspection systems [[Paper]](https://www.sciencedirect.com/science/article/pii/S0969806X21001626?casa_token=oQnnKwLnYqIAAAAA:cVnclMgMt-24YQEl8dlErCzgMDZlvGC35CF6cddeil5qxxQ0ZhY05P74P0tcBN_M5I4iUk7dSg) #### 3D - CTIMS: Automated Defect Detection Framework Using Computed Tomography [[Paper]](https://www.mdpi.com/2076-3417/12/4/2175) ### 2021 [^[top]](#scroll-paper) #### 2D - Super-resolution network for x-ray security inspection [[Paper]](https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12281/2616535/Super-resolution-network-for-x-ray-security-inspection/10.1117/12.2616535.short?SSO=1) - Information-exchange Enhanced Feature Pyramid Network (IEFPN) for Detecting Prohibited Items in X-ray Security Images [[Paper]](https://ieeexplore.ieee.org/document/9674494) - Learning-Based Image Synthesis for Hazardous Object Detection in X-Ray Security Applications [[Paper]](https://ieeexplore.ieee.org/document/9552004) - X-ray Security Inspection Image Detection Algorithm Based on Improved YOLOv4 [[Paper]](https://ieeexplore.ieee.org/document/9645636) - A YOLOv5s-SE model for object detection in X-ray security images [[Paper]](https://ieeexplore.ieee.org/document/9624606) - Prohibited Items Detection in X-ray Images in YOLO Network [[Paper]](https://ieeexplore.ieee.org/document/9594145) - Automatic and Robust Object Detection in X-Ray Baggage Inspection Using Deep Convolutional Neural Networks [[Paper]](https://ieeexplore.ieee.org/document/9209096) - Classify and Localize Threat Items in X-Ray Imagery With Multiple Attention Mechanism and High-Resolution and High-Semantic Features [[Paper]](https://ieeexplore.ieee.org/document/9513650) - Raw Data Processing Using Modern Hardware for Inspection of Objects in X-Ray Baggage Inspection Systems [[Paper]](https://ieeexplore.ieee.org/document/9417094) - Temporal Fusion Based Mutli-scale Semantic Segmentation for Detecting Concealed Baggage Threats [[Paper]](https://ieeexplore.ieee.org/document/9658932) - Automatic Threat Detection Using Deep Neural Networks [[Paper]](https://ieeexplore.ieee.org/document/9719550) - Towards Real-world X-ray Security Inspection: A High-Quality Benchmark And Lateral Inhibition Module For Prohibited Items Detection [[Paper]](https://ieeexplore.ieee.org/document/9710060) - A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband Items [[Paper]](https://arxiv.org/pdf/2201.02560.pdf) - Deep Fusion Driven Semantic Segmentation for the Automatic Recognition of Concealed Contraband Items [[Paper]](https://link.springer.com/chapter/10.1007%2F978-3-030-73689-7_53) - Brittle Features May Help Anomaly Detection [[Paper]](https://arxiv.org/abs/2104.10453) - Deep Learning-Based X-Ray Baggage Hazardous Object Detection – An FPGA Implementation [[Paper]](https://www.iieta.org/journals/ria/paper/10.18280/ria.350510) - Operationalizing Convolutional Neural Network Architectures for Prohibited Object Detection in X-Ray Imagery [[Paper]](https://arxiv.org/abs/2110.04906) - Towards Automatic Threat Detection: A Survey of Advances of Deep Learning within X-ray Security Imaging [[Paper]](https://arxiv.org/abs/2001.01293) - On the Impact of Using X-Ray Energy Response Imagery for Object Detection via Convolutional Neural Networks [[Paper]](https://arxiv.org/abs/2108.12505) - Towards Real-World Prohibited Item Detection: A Large-Scale X-ray Benchmark [[Paper]](https://arxiv.org/pdf/2108.07020.pdf) - PANDA: Perceptually Aware Neural Detection of Anomalies [[Paper]](https://arxiv.org/abs/2104.13702) - Tensor Pooling Driven Instance Segmentation Framework for Baggage Threat Recognition [[Paper]](https://arxiv.org/abs/2108.09603) - Unsupervised Anomaly Instance Segmentation for Baggage Threat Recognition [[Paper]](https://arxiv.org/abs/2107.07333) - Symmetric Triangle Network for Object Detection Within X-ray Baggage Security Imagery [[Paper]](https://ieeexplore.ieee.org/document/9533991) - Anomaly Detection in X-ray Security Imaging: a Tensor-Based Learning Approach [[Paper]](https://ieeexplore.ieee.org/document/9534034) - Automated Threat Objects Detection with Synthetic Data for Real-Time X-ray Baggage Inspection [[Paper]](https://ieeexplore.ieee.org/document/9533928) - Evaluating GAN-Based Image Augmentation for Threat Detection in Large-Scale Xray Security Images [[Paper]](https://www.mdpi.com/2076-3417/11/1/36) - An X-ray Image Enhancement Algorithm for Dangerous Goods in Airport Security Inspection [[Paper]](https://ieeexplore.ieee.org/document/9407728/metrics#metrics) - Baggage Threat Detection Under Extreme Class Imbalance [[Paper]](https://ieeexplore.ieee.org/abstract/document/9787472) - Detecting Overlapped Objects in X-Ray Security Imagery by a Label-Aware Mechanism [[Paper]](https://ieeexplore.ieee.org/document/9722843) #### 3D CT - Contraband Materials Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery [[Paper]](https://arxiv.org/abs/2012.11753) - On the Evaluation of Semi-Supervised 2D Segmentation for Volumetric 3D Computed Tomography Baggage Security Screening [[Paper]](https://breckon.org/toby/publications/papers/wang21segmentation.pdf) - SliceNets — A Scalable Approach for Object Detection in 3D CT Scans [[Paper]](https://ieeexplore.ieee.org/document/9423392) - DEBISim: A simulation pipeline for dual energy CT-based baggage inspection systems [[Paper]](https://content.iospress.com/articles/journal-of-x-ray-science-and-technology/xst200808) ### 2020 [^[top]](#scroll-paper) #### 2D - Learning-based Material Classification in X-ray Security Images [[Paper]](https://www.scitepress.org/Link.aspx?doi=10.5220/0008951702840291) - Multi-label X-ray Imagery Classification via Bottom-up Attention and Meta Fusion [[Paper]](https://openaccess.thecvf.com/content/ACCV2020/html/Hu_Multi-label_X-ray_Imagery_Classification_via_Bottom-up_Attention_and_Meta_Fusion_ACCV_2020_paper.html) - Multi-view Object Detection Using Epipolar Constraints within Cluttered X-ray Security Imagery [[Paper]](https://breckon.org/toby/publications/papers/isaac20multiview.pdf) - Occluded Prohibited Items Detection: an X-ray Security Inspection Benchmark and De-occlusion Attention Module [[Paper]](https://arxiv.org/abs/2004.08656) - Trainable Structure Tensors for Autonomous Baggage Threat Detection Under Extreme Occlusion [[Paper]](https://arxiv.org/abs/2009.13158) - Cascaded Structure Tensor Framework for Robust Identification of Heavily Occluded Baggage Items from X-ray Scans [[Paper]](https://arxiv.org/abs/2004.06780) - Automatic Threat Detection in Baggage Security Imagery using Deep Learning Models [[Paper]](https://ieeexplore.ieee.org/document/9342691) - Automatic Threat Detection in Single, Stereo (Two) and Multi View X-Ray Images [[Paper]](https://ieeexplore.ieee.org/document/9342253) - Detecting Prohibited Items in X-Ray Images: a Contour Proposal Learning Approach [[Paper]](https://ieeexplore.ieee.org/document/9190711) - Background Adaptive Faster R-CNN for Semi-Supervised Convolutional Object Detection of Threats in X-Ray Images [[Paper]](https://arxiv.org/abs/2010.01202) - X-Ray Baggage Inspection With Computer Vision: A Survey [[Paper]](https://ieeexplore.ieee.org/document/9162101) - Data Augmentation of X-Ray Images in Baggage Inspection Based on Generative Adversarial Networks [[Paper]](https://ieeexplore.ieee.org/document/9087880) #### 3D CT - Multi-Class 3D Object Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery [[Paper]](https://arxiv.org/abs/2008.01218) - On the Evaluation of Prohibited Item Classification and Detection in Volumetric 3D Computed Tomography Baggage Security Screening Imagery [[Paper]](https://arxiv.org/abs/2003.12625) - A Reference Architecture for Plausible Threat Image Projection (TIP) Within 3D X-ray Computed Tomography Volumes [[Paper]](https://arxiv.org/abs/2001.05459) - An Approach for Adaptive Automatic Threat Recognition Within 3D Computed Tomography Images for Baggage Security Screening [[Paper]](https://arxiv.org/abs/1903.10604) ### 2019 [^[top]](#scroll-paper) #### 2D - Evaluating the Transferability and Adversarial Discrimination of Convolutional Neural Networks for Threat Object Detection and Classification within X-Ray Security Imagery [[Paper]](https://arxiv.org/abs/1911.08966) - On the Impact of Object and Sub-Component Level Segmentation Strategies for Supervised Anomaly Detection within X-Ray Security Imagery [[Paper]](https://arxiv.org/abs/1911.08216) - Using Deep Neural Networks to Address the Evolving Challenges of Concealed Threat Detection within Complex Electronic Items [[Paper]](https://breckon.org/toby/publications/papers/bhowmik19electronics.pdf) - On the Use of Deep Learning for the Detection of Firearms in X-ray Baggage Security Imagery [[Paper]](https://breckon.org/toby/publications/papers/gaus19firearms.pdf) - The Good, the Bad and the Ugly: Evaluating Convolutional Neural Networks for Prohibited Item Detection Using Real and Synthetically Composite X-ray Imagery [[Paper]](https://arxiv.org/abs/1909.11508) - Evaluating a Dual Convolutional Neural Network Architecture for Object-wise Anomaly Detection in Cluttered X-ray Security Imagery [[Paper]](https://breckon.org/toby/publications/papers/gaus19anomaly.pdf) - Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection [[Paper]](https://arxiv.org/abs/1901.08954) - An evaluation of deep learning based object detection strategies for threat object detection in baggage security imagery [[Paper]](https://www.sciencedirect.com/science/article/pii/S016786551930011X) - Deep Convolutional Neural Network Based Object Detector for X-Ray Baggage Security Imagery [[Paper]](https://ieeexplore.ieee.org/abstract/document/8995335) - Automated firearms detection in cargo x-ray images using RetinaNet [[Paper]](https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10999/109990P/Automated-firearms-detection-in-cargo-x-ray-images-using-RetinaNet/10.1117/12.2517817.full?SSO=1) - Toward Automatic Threat Recognition for Airport X-ray Baggage Screening with Deep Convolutional Object Detection [[Paper]](https://arxiv.org/abs/1912.06329) - “Unexpected Item in the Bagging Area”: Anomaly Detection in X-Ray Security Images [[Paper]](https://ieeexplore.ieee.org/document/8537982) - Limits on transfer learning from photographic image data to X-ray threat detection [[Paper]](https://www.semanticscholar.org/paper/Limits-on-transfer-learning-from-photographic-image-Caldwell-Griffin/7e7e445bbb757c4ec9165505925e48b0f94a92ad) - Data Augmentation for X-Ray Prohibited Item Images Using Generative Adversarial Networks [[Paper]](https://ieeexplore.ieee.org/document/8654640) - Modified Adaptive Implicit Shape Model for Object Detection [[Paper]](https://link.springer.com/chapter/10.1007/978-3-030-36802-9_17) - Graph clustering and variational image segmentation for automated firearm detection in X-ray images [[Paper]](https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5198) - Semantic Segmentation for Prohibited Items in Baggage Inspection [[Paper]](https://link.springer.com/chapter/10.1007/978-3-030-36189-1_41#:~:text=Semantic%20segmentation%20is%20a%20branch,open%20the%20baggage%20for%20inspection.) - Application of Machine Learning Methods for Material Classification with Multi-energy X-Ray Transmission Images [[Paper]](https://link.springer.com/chapter/10.1007/978-3-030-24274-9_17) - Handgun Detection in Single-Spectrum Multiple X-ray Views Based on 3D Object Recognition [[Paper]](https://link.springer.com/article/10.1007/s10921-019-0602-9) #### 3D CT - On the Relevance of Denoising and Artefact Reduction in 3D Segmentation and Classification within Complex Computed Tomography Imagery [[Paper]](https://breckon.org/toby/publications/papers/mouton19relevance.pdf) ### 2018 [^[top]](#scroll-paper) #### 2D - On Using Deep Convolutional Neural Network Architectures for Automated Object Detection and Classification within X-ray Baggage Security Imagery [[Paper]](https://breckon.org/toby/publications/papers/akcay18architectures.pdf) - GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training [[Paper]](https://arxiv.org/abs/1805.06725) - Multi-view X-ray R-CNN [[Paper]](https://arxiv.org/abs/1810.02344) - A GAN-Based Image Generation Method for X-Ray Security Prohibited Items [[Paper]](https://link.springer.com/chapter/10.1007/978-3-030-03398-9_36) - Prohibited Item Detection in Airport X-Ray Security Images via Attention Mechanism Based CNN [[Paper]](https://link.springer.com/chapter/10.1007/978-3-030-03335-4_37) - Convolutional Neural Networks for Automatic Threat Detection in Security X-Ray Images [[Paper]](https://ieeexplore.ieee.org/document/8614074) - Automatic threat recognition of prohibited items at aviation checkpoint with x-ray imaging: a deep learning approach [[Paper]](https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10632/1063203/Automatic-threat-recognition-of-prohibited-items-at-aviation-checkpoint-with/10.1117/12.2309484.full?webSyncID=8531ab0d-3a6b-03c9-7c00-9b6bcd746b80&sessionGUID=d8e8abee-aed6-ae05-c117-aac5a9199362) #### 3D CT - Consensus relaxation on materials of interest for adaptive ATR in CT images of baggage [[Paper]](https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10632/106320E/Consensus-relaxation-on-materials-of-interest-for-adaptive-ATR-in/10.1117/12.2309839.full) - Adaptive Target Recognition: A Case Study Involving Airport Baggage Screening [[Paper]](https://arxiv.org/abs/1811.04772) ### Earlier [^[top]](#scroll-paper) #### 2D - An Evaluation Of Region Based Object Detection Strategies Within X-Ray Baggage Security Imagery [[Paper]](https://breckon.org/toby/publications/papers/akcay17region.pdf) - On using Feature Descriptors as Visual Words for Object Detection within X-ray Baggage Security Screening [[Paper]](https://breckon.org/toby/publications/papers/kundegorski16xray.pdf) - Transfer Learning Using Convolutional Neural Networks For Object Classification Within X-Ray Baggage Security Imagery [[Paper]](https://breckon.org/toby/publications/papers/akcay16transfer.pdf) - Improving Feature-based Object Recognition for X-ray Baggage Security Screening using Primed Visual Words [[Paper]](https://breckon.org/toby/publications/papers/turcsany13xray.pdf) - A Combinational Approach to the Fusion, De-noising and Enhancement of Dual-Energy X-Ray Luggage Images [[Paper]](https://ieeexplore.ieee.org/document/1565297) - Improving Weapon Detection In Single Energy X-ray Images Through Pseudocoloring [[Paper]](https://ieeexplore.ieee.org/abstract/document/1715507) - A review of X-ray explosives detection techniques for checked baggage [[Paper]](https://www.sciencedirect.com/science/article/pii/S0969804312000127) - A Logarithmic X-Ray Imaging Model for Baggage Inspection: Simulation and Object Detection [[Paper]](https://ieeexplore.ieee.org/document/8014771) - Automatic Defect Recognition in X-Ray Testing Using Computer Vision [[Paper]](https://ieeexplore.ieee.org/document/7926702) - Modern Computer Vision Techniques for X-Ray Testing in Baggage Inspection[[Paper]](https://ieeexplore.ieee.org/document/7775025) - Inspection of Complex Objects Using Multiple-X-Ray Views [[Paper]](https://ieeexplore.ieee.org/document/6782468) - Automated X-Ray Object Recognition Using an Efficient Search Algorithm in Multiple Views [[Paper]](https://ieeexplore.ieee.org/document/6595901) - X-Ray Testing by Computer Vision [[Paper]](https://ieeexplore.ieee.org/document/6595900) - Automated detection in complex objects using a tracking algorithm in multiple X-ray views [[Paper]](https://ieeexplore.ieee.org/document/5981715) - Threat Objects Detection in X-ray Images Using an Active Vision Approach [[Paper]](https://link.springer.com/article/10.1007/s10921-017-0419-3) - Object recognition in X-ray testing using an efficient search algorithm in multiple views [[Paper]](https://www.ingentaconnect.com/content/bindt/insight/2017/00000059/00000002/art00008;jsessionid=1n6a28jhds21c.x-ic-live-02) - Modern Computer Vision Techniques for X-Ray Testing in Baggage Inspection [[Paper]](https://ieeexplore.ieee.org/document/7775025) - Automated Detection of Threat Objects Using Adapted Implicit Shape Model [[Paper]](https://ieeexplore.ieee.org/document/7123190) - A review of X-ray explosives detection techniques for checked baggage [[Paper]](https://www.sciencedirect.com/science/article/pii/S0969804312000127) - Explosives detection systems (EDS) for aviation security [[Paper]](https://www.sciencedirect.com/science/article/pii/S0165168402003912) #### 3D CT - Geometrical Approach for the Automatic Detection of Liquid Surfaces in 3D Computed Tomography Baggage Imagery [[Paper]](https://breckon.org/toby/publications/papers/chermak15liquids.pdf) - Materials-Based 3D Segmentation of Unknown Objects from Dual-Energy Computed Tomography Imagery in Baggage Security Screening [[Paper]](https://breckon.org/toby/publications/papers/mouton15segmentation.pdf) - Object Classification in 3D Baggage Security Computed Tomography Imagery using Visual Codebooks [[Paper]](https://breckon.org/toby/publications/papers/flitton15codebooks.pdf) - 3D Object Classification in Baggage Computed Tomography Imagery using Randomised Clustering Forests [[Paper]](https://breckon.org/toby/publications/papers/mouton14randomised.pdf) - Investigating Existing Medical CT Segmentation Techniques within Automated Baggage and Package Inspection [[Paper]](https://breckon.org/toby/publications/papers/megherbi13segmentation.pdf) - Radon Transform based Metal Artefacts Generation in 3D Threat Image Projection [[Paper]](https://breckon.org/toby/publications/papers/megherbi13radon.pdf) - A Comparison of 3D Interest Point Descriptors with Application to Airport Baggage Object Detection in Complex CT Imagery [[Paper]](https://breckon.org/toby/publications/papers/flitton13interestpoint.pdf) - A Distance Weighted Method for Metal Artefact Reduction in CT [[Paper]](https://breckon.org/toby/publications/papers/mouton13mar.pdf) - An Experimental Survey of Metal Artefact Reduction in Computed Tomography [[Paper]](https://breckon.org/toby/publications/papers/mouton13survey.pdf) - An Evaluation of CT Image Denoising Techniques Applied to Baggage Imagery Screening [[Paper]](https://breckon.org/toby/publications/papers/mouton13denoising.pdf) - Fully Automatic 3D Threat Image Projection: Application to Densely Cluttered 3D Computed Tomography Baggage Images [[Paper]](https://breckon.org/toby/publications/papers/megherbi12tip.pdf) - A Comparison of Classification Approaches for Threat Detection in CT based Baggage Screening [[Paper]](https://breckon.org/toby/publications/papers/megherbi12baggage.pdf) - A Novel Intensity Limiting Approach to Metal Artefact Reduction in 3D CT Baggage Imagery [[Paper]](https://breckon.org/toby/publications/papers/mouton12mar.pdf) - A 3D Extension to Cortex Like Mechanisms for 3D Object Class Recognition [[Paper]](https://breckon.org/toby/publications/papers/flitton12cortex.pdf) - Object Recognition using 3D SIFT in Complex CT Volumes [[Paper]](https://breckon.org/toby/publications/papers/flitton10baggage.pdf) - A Classifier based Approach for the Detection of Potential Threats in CT based Baggage Screening [[Paper]](https://breckon.org/toby/publications/papers/megherbi10baggage.pdf) - A review of automated image understanding within 3D baggage computed tomography security screening [[Paper]](https://breckon.org/toby/publications/papers/mouton15review.pdf) - A volumetric object detection framework with dual-energy CT [[Paper]](https://ieeexplore.ieee.org/document/4774641) - Exact Reconstruction for Dual Energy Computed Tomography Using an H-L Curve Method [[Paper]](https://ieeexplore.ieee.org/document/4179793) - Automatic segmentation of CT scans of checked baggage [[Paper]](https://www.stratovan.com/sites/default/files/AutomaticSegmentationOfCtScansOfCheckedBaggage.pdf) - Automatic Segmentation of Unknown Objects, with Application to Baggage Security [[Paper]](https://link.springer.com/chapter/10.1007/978-3-642-33709-3_31) - ALERT Strategic Studies [[Paper]]() - Joint metal artifact reduction and segmentation of CT images using dictionary-based image prior and continuous-relaxed potts model [[Paper]](https://ieeexplore.ieee.org/document/7350909) - Using Threat Image Projection Data Forassessing Individual Screener Performance [[Paper]](https://www.witpress.com/elibrary/wit-transactions-on-the-built-environment/82/15153) - 3D threat image projection [[Paper]](https://www.spiedigitallibrary.org/conference-proceedings-of-spie/6805/680508/3D-threat-image-projection/10.1117/12.766432.full?SSO=1) - Learning-Based Object Identification and Segmentation Using Dual-Energy CT Images for Security [[Paper]](https://ieeexplore.ieee.org/document/7159062) ## :frog: Reference If you use this repo and like it, use this to cite it: ```tex @misc{xray-vision, title={Xray-Vision: Brief history of X-ray security imaging in Computer Vision}, author={Neelanjan Bhowmik}, year={2024}, url={https://github.com/NeelBhowmik/xray} } ``` ## :rocket: Contribute Welcome to our lively repository - and you're invited to join the party! Feel free to contribute! If you spot a missing paper/dataset - create an [issue](https://github.com/NeelBhowmik/xray/issues). Together, we'll make this repo the coolest gathering spot for all things knowledge 📚