10 papers
MATERO-RCA: Mode-Aware Trajectory-Level Energy-Based Root-Set Optimization for Industrial Root Cause Analysis
Chengyu Tao, Chunxi Huang, Runquan Xiao
Root cause analysis (RCA) for contextual anomalies in industrial time series is challenging because responses depend jointly on control commands, operating states, and coupled phys…
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…
IAENet: An Importance-Aware Ensemble Model for 3D Point Cloud-Based Anomaly Detection
Xuanming Cao, Chengyu Tao, Yifeng Cheng +1
Surface anomaly detection is pivotal for ensuring product quality in industrial manufacturing. While 2D image-based methods have achieved remarkable success, 3D point cloud-based d…
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…