11.2.3.1 3-D Anomaly Detection

Summers, R.M.[Ronald M.], Selbie, S.[Scott], Malley, J.D.[James D.], Pusanik, L.M.[Lynne M.],
Method for segmenting medical images and detecting surface anomalies in anatomical structures,
US_Patent6,556,696, Apr 29, 2003
WWW Link. BibRef 0304

Zavrtanik, V.[Vitjan], Kristan, M.[Matej], Skocaj, D.[Danijel],
Keep DRÆMing: Discriminative 3D anomaly detection through anomaly simulation,
PRL(181), 2024, pp. 113-119.
Elsevier DOI 2405
3D anomaly detection, Anomaly simulation, Discriminative anomaly detection BibRef

Li, P.[Pulin], Wu, G.C.[Guo-Cheng], Zhou, Y.J.[Yan-Jie], Leng, J.[Jiewu],
Enhancing random surface anomaly detection in real-world using a four-stage one-class approach,
PRL(194), 2025, pp. 32-40.
Elsevier DOI 2506
Industrial anomaly detection, Unsupervised learning, Adapter tuning, Mechanical manufacturing, Real-world applications BibRef

Wang, C.J.[Cheng-Jie], Zhu, H.[Haokun], Peng, J.L.[Jin-Long], Wang, Y.[Yue], Yi, R.[Ran], Wu, Y.S.[Yun-Sheng], Ma, L.Z.[Li-Zhuang], Zhang, J.N.[Jiang-Ning],
M3DM-NR: RGB-3D Noisy-Resistant Industrial Anomaly Detection via Multimodal Denoising,
PAMI(47), No. 11, November 2025, pp. 9981-9993.
IEEE DOI 2510
Anomaly detection, Feature extraction, Noise measurement, Training, Noise, Image reconstruction, unsupervised learning BibRef

Wang, Y.[Yue], Peng, J.L.[Jin-Long], Zhang, J.N.[Jiang-Ning], Yi, R.[Ran], Wang, Y.B.[Ya-Biao], Wang, C.J.[Cheng-Jie],
Multimodal Industrial Anomaly Detection via Hybrid Fusion,
CVPR23(8032-8041)
IEEE DOI 2309
BibRef

Zhang, R.[Ruifan], Hu, H.M.[Hai-Miao],
A Multi-Category Anomaly Editing Network With Correlation Exploration and Voxel-Level Attention for Unsupervised Surface Anomaly Detection,
IP(34), 2025, pp. 7152-7167.
IEEE DOI 2511
Image reconstruction, Feature extraction, Anomaly detection, Surface reconstruction, Training, Correlation, Semantics, voxel level attention BibRef

Wu, L.C.[Lin-Chun], Ning, J.[Jian], Zou, Q.[Qin],
Anomaly-aware Siamese comparative transformer for 3D anomaly detection,
PRL(207), 2026, pp. 137-144.
Elsevier DOI 2608
Anomaly aware modeling, Siamese transformer, Point cloud anomaly detection BibRef

Gao, H.[Hui], Zhao, W.L.[Wen-Long], Zhong, Y.Z.[Yu-Zhong], Wang, M.N.[Mao-Ning], Zhang, J.W.[Jian-Wei],
SimpleZ3D: A simple framework for zero-shot 3D industrial anomaly detection,
PR(180), 2026, pp. 114237.
Elsevier DOI Code:
WWW Link. 2608
2D/3D industrial anomaly detection, Zero-shot 2D/3D industrial anomaly detection, Simulated multimodal BibRef

Ning, J.[Jian], Zou, Q.[Qin], Wu, L.[Linchun], Yue, Y.H.[Yuan-Hao], Li, K.[Kunmo], Chen, S.[Shoubin], Wang, Z.Y.[Zhong-Yuan],
Physics-inspired pseudo anomaly generation and prototype feature guidance for 3D anomaly detection,
PR(180), 2026, pp. 114391.
Elsevier DOI Code:
WWW Link. 2609
Physics-inspired modeling, Anomaly generation, Anomaly detection, Point cloud BibRef

Ye, J.A.[Jian-An], Zhao, W.G.[Wei-Guang], Yang, X.[Xi], Cheng, G.L.[Guang-Liang], Huang, K.[Kaizhu],
PO3AD: Predicting Point Offsets toward Better 3D Point Cloud Anomaly Detection,
CVPR25(1353-1362)
IEEE DOI Code:
WWW Link. 2508
Point cloud compression, Training, Measurement, Data visualization, Feature extraction, Vectors, Data models, Anomaly detection, 3d point cloud BibRef

Zhu, W.B.[Wen-Bing], Wang, L.[Lidong], Zhou, Z.Q.[Zi-Qing], Wang, C.J.[Cheng-Jie], Pan, Y.R.[Yu-Rui], Zhang, R.[Ruoyi], Chen, Z.[Zhuhao], Cheng, L.J.[Lin-Jie], Gao, B.B.[Bin-Bin], Zhang, J.N.[Jiang-Ning], Gan, Z.Y.[Zhen-Ye], Wang, Y.X.[Yu-Xie], Chen, Y.L.[Yu-Long], Qian, S.G.[Shu-Guang], Chi, M.M.[Ming-Min], Peng, B.[Bo], Ma, L.Z.[Li-Zhuang],
Real-IAD D3: A Real-World 2D/Pseudo-3D/3D Dataset for Industrial Anomaly Detection,
CVPR25(15214-15223)
IEEE DOI Code:
WWW Link. 2508
Point cloud compression, Image resolution, Face recognition, Machine vision, Feature extraction, Robustness, Complexity theory, Anomaly detection BibRef

Uchida, A.[Akira], Ikehata, S.[Satoshi], Yoshida, Y.[Yuichi], Sato, I.[Ikuro],
Measuring Distortion Strength with Dewarping Diffusion Models in Anomaly Detection,
ICIP25(2157-2162)
IEEE DOI Code:
WWW Link. 2601
Surface reconstruction, Deformation, Diffusion processes, Inspection, Distortion, Diffusion models, Robustness, Transistors BibRef

Zhou, Z.Y.[Zhe-Yuan], Wang, L.[Le], Fang, N.[Naiyu], Wang, Z.L.[Zi-Li], Qiu, L.[Lemiao], Zhang, S.[Shuyou],
R3D-AD: Reconstruction via Diffusion for 3d Anomaly Detection,
ECCV24(XXXVI: 91-107).
Springer DOI 2412
BibRef

Tu, Y.P.[Yuan-Peng], Zhang, B.S.[Bo-Shen], Liu, L.[Liang], Li, Y.X.[Yu-Xi], Zhang, J.N.[Jiang-Ning], Wang, Y.B.[Ya-Biao], Wang, C.J.[Cheng-Jie], Zhao, C.R.[Cai-Rong],
Self-Supervised Feature Adaptation for 3D Industrial Anomaly Detection,
ECCV24(II: 75-91).
Springer DOI 2412
BibRef

Kruse, M.[Mathis], Rudolph, M.[Marco], Woiwode, D.[Dominik], Rosenhahn, B.[Bodo],
SplatPose & Detect: Pose-Agnostic 3D Anomaly Detection,
VAND24(3950-3960)
IEEE DOI 2410
Training, Point cloud compression, Pose estimation, Training data, Production, Neural radiance field, anomaly detection, anomaly segmentation BibRef

Zhao, J.H.[Jin-Hui], Gao, H.X.[Hong-Xia], Liu, T.T.[Tong-Tong],
Surface Anomaly Detection with Anomalous Feature Restriction And Difference-Aware Enhancement,
ICIP24(1377-1383)
IEEE DOI 2411
Location awareness, Image segmentation, Surface reconstruction, Inspection, Feature extraction, Product design, Quality assessment, Difference-aware enhancement BibRef

Li, W.Q.[Wen-Qiao], Xu, X.H.[Xiao-Hao], Gu, Y.[Yao], Zheng, B.Z.[Bo-Zhong], Gaol, S.H.[Sheng-Hua], Wu, Y.[Yingna],
Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network,
CVPR24(22207-22216)
IEEE DOI Code:
WWW Link. 2410
Point cloud compression, Training, Location awareness, Solid modeling, Adaptation models, Benchmark testing, Anomaly Detection 3D Vision Self-Supervised BibRef

Zavrtanik, V.[Vitjan], Kristan, M.[Matej], Skocaj, D.[Danijel],
Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth Simulation,
WACV24(2153-2161)
IEEE DOI Code:
WWW Link. 2404
Training, Solid modeling, Codes, Information retrieval, Feature extraction, Algorithms, Machine learning architectures, and algorithms BibRef

Horwitz, E.[Eliahu], Hoshen, Y.[Yedid],
Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection,
VAND23(2968-2977)
IEEE DOI 2309
BibRef

Bergmann, P.[Paul], Sattlegger, D.[David],
Anomaly Detection in 3D Point Clouds using Deep Geometric Descriptors,
WACV23(2612-2622)
IEEE DOI 2302
Point cloud compression, Training, Location awareness, Runtime, Protocols, Memory management, 3D computer vision BibRef

Zavrtanik, V.[Vitjan], Kristan, M.[Matej], Skocaj, D.[Danijel],
DRÆM: A discriminatively trained reconstruction embedding for surface anomaly detection,
ICCV21(8310-8319)
IEEE DOI 2203
Location awareness, Surface reconstruction, Computational modeling, Feature extraction, Task analysis, Vision applications and systems BibRef

Marani, R., Petitti, A., Attolico, M., Cicirelli, G., Milella, A., d'Orazio, T.,
Disparity Image Analysis for 3D Characterization of Surface Anomalies,
CIAP19(II:14-23).
Springer DOI 1909
BibRef

Bürger, F.[Fabian], Pauli, J.[Josef],
Unsupervised Segmentation of Anomalies in Sequential Data, Images and Volumetric Data Using Multiscale Fourier Phase-Only Analysis,
SCIA13(44-53).
Springer DOI 1311
BibRef

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Surfaces and Range Data, Normal Vector, Surface Normal .