7 papers
Align3D-AD: Cross-Modal Feature Alignment and Dual-Prompt Learning for Zero-shot 3D Anomaly Detection
Letian Bai, Xuanming Cao, Juan Du +1
Zero-shot 3D anomaly detection aims to identify anomalies without access to training data from target categories. However, existing methods mainly rely on projecting 3D observation…
FORGE: Fine-grained Multimodal Evaluation for Manufacturing Scenarios
Xiangru Jian, Hao Xu, Wei Pang +13
The manufacturing sector is increasingly adopting Multimodal Large Language Models (MLLMs) to transition from simple perception to autonomous execution, yet current evaluations fai…
SGANet: Semantic and Geometric Alignment for Multimodal Multi-view Anomaly Detection
Letian Bai, Chengyu Tao, Juan Du
Multi-view anomaly detection aims to identify surface defects on complex objects using observations captured from multiple viewpoints. However, existing unsupervised methods often…
GSF-MIAD: Geometry-Guided Score Fusion for Multimodal Industrial Anomaly Detection
Chengyu Tao, Xuanming Cao, Juan Du
Industrial quality inspection plays a critical role in modern manufacturing by identifying defective products during production. While single-modality approaches using either 3D po…
Deep Subspace Learning for Surface Anomaly Classification Based on 3D Point Cloud Data
Xuanming Cao, Chengyu Tao, Juan Du
Surface anomaly classification is critical for manufacturing system fault diagnosis and quality control. However, the following challenges always hinder accurate anomaly classifica…
Ano-SuPs: Multi-size anomaly detection for manufactured products by identifying suspected patches
Hao Xu, Juan Du, Andi Wang +1
Image-based systems have gained popularity owing to their capacity to provide rich manufacturing status information, low implementation costs and high acquisition rates. However, t…