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20242026
most citedDeep Subspace Learning for Surface Anomaly Classification Based on 3D Point Cloud Data

1 citations · 2 across the 5 of their papers we have counts for

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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.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…

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…