3 papers
cs.CV2026
DMP-3DAD: Cross-Category 3D Anomaly Detection via Realistic Depth Map Projection with Few Normal Samples
Zi Wang, Katsuya Hotta, Koichiro Kamide +4
Cross-category anomaly detection for 3D point clouds aims to determine whether an unseen object belongs to a target category using only a few normal examples. Most existing methods…
cs.CV2023
Multilevel Saliency-Guided Self-Supervised Learning for Image Anomaly Detection
Jianjian Qin, Chunzhi Gu, Jun Yu +1
Anomaly detection (AD) is a fundamental task in computer vision. It aims to identify incorrect image data patterns which deviate from the normal ones. Conventional methods generall…
cs.CV2023
Multi-Scale Distillation for RGB-D Anomaly Detection on the PD-REAL Dataset
Jianjian Qin, Chao Zhang, Chunzhi Gu +5
We present PD-REAL, a novel large-scale dataset for unsupervised anomaly detection (AD) in the 3D domain. It is motivated by the fact that 2D-only representations in the AD task ma…