A Survey on RGB, 3D, and Multimodal Approaches for Unsupervised Industrial Anomaly Detection

Y Lin, Y Chang, X Tong, J Yu, A Liotta, G Huang… - arxiv preprint arxiv …, 2024 - arxiv.org
In the advancement of industrial informatization, Unsupervised Industrial Anomaly Detection
(UIAD) technology effectively overcomes the scarcity of abnormal samples and significantly …

Uni-3DAD: Gan-inversion aided universal 3D anomaly detection on model-free products

J Liu, S Mou, N Gaw, Y Wang - Expert Systems with Applications, 2025 - Elsevier
Anomaly detection is a long-standing challenge in manufacturing systems, aiming to locate
surface defects and improve product quality. Traditionally, anomaly detection has relied on …

Revisiting Multimodal Fusion for 3D Anomaly Detection from an Architectural Perspective

K Long, G **e, L Ma, J Liu, Z Lu - arxiv preprint arxiv:2412.17297, 2024 - arxiv.org
Existing efforts to boost multimodal fusion of 3D anomaly detection (3D-AD) primarily
concentrate on devising more effective multimodal fusion strategies. However, little attention …

PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection

Q Zhou, J Yan, S He, W Meng, J Chen - arxiv preprint arxiv:2410.00320, 2024 - arxiv.org
Zero-shot (ZS) 3D anomaly detection is a crucial yet unexplored field that addresses
scenarios where target 3D training samples are unavailable due to practical concerns like …