most citedDeep Subspace Learning for Surface Anomaly Classification Based on 3D Point Cloud Data

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

cs.CV2025

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…

eess.IV2025

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…