activity
20232026
most citedGSF-MIAD: Geometry-Guided Score Fusion for Multimodal Industrial Anomaly Detection

1 citations · 3 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

eess.IV2025★ 1 cited

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…

stat.ML2025★ 1 cited

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…

cs.CV2024

A Novel Representation of Periodic Pattern and Its Application to Untrained Anomaly Detection

Peng Ye, Chengyu Tao, Juan Du

There are a variety of industrial products that possess periodic textures or surfaces, such as carbon fiber textiles and display panels. Traditional image-based quality inspection…

eess.IV2024★ 1 cited

F2PAD: A General Optimization Framework for Feature-Level to Pixel-Level Anomaly Detection

Chengyu Tao, Hao Xu, Juan Du

Image-based inspection systems have been widely deployed in manufacturing production lines. Due to the scarcity of defective samples, unsupervised anomaly detection that only lever…

cs.CV2024

3D-CSAD: Untrained 3D Anomaly Detection for Complex Manufacturing Surfaces

Xuanming Cao, Chengyu Tao, Juan Du

The surface quality inspection of manufacturing parts based on 3D point cloud data has attracted increasing attention in recent years. The reason is that the 3D point cloud can cap…

stat.ML2023

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…