5 papers
Diffuse to Detect: A Generalizable Framework for Anomaly Detection with Diffusion Models Applications to UAVs and Beyond
Mingze Gong, Juan Du, Jianbang You
Anomaly detection in complex, high-dimensional data, such as UAV sensor readings, is essential for operational safety but challenging for existing methods due to their limited sens…
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…
HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection
Jiaping Cao, Kangkang Zhou, Juan Du
Video anomaly detection is a fundamental task in video surveillance, with broad applications in public safety and intelligent monitoring systems. Although previous methods leverage…
Position: Untrained Machine Learning for Anomaly Detection by using 3D Point Cloud Data
Juan Du, Dongheng Chen
Anomaly detection based on 3D point cloud data is an important research problem and receives more and more attention recently. Untrained anomaly detection based on only one sample…
3D-PNAS: 3D Industrial Surface Anomaly Synthesis with Perlin Noise
Yifeng Cheng, Juan Du
Large pretrained vision foundation models have shown significant potential in various vision tasks. However, for industrial anomaly detection, the scarcity of real defect samples p…