1 citations · 2 across the 4 of their papers we have counts for
Showing 2026 · cs.CVShow all
2 papers · 2 filters
cs.CV2026
VT-3DAD: Cross-Category 3D Anomaly Detection via Visual-Text Normal Space Alignment
Zi Wang, Katsuya Hotta, Yawen Zou +4
Few-shot cross-category 3D anomaly detection aims to determine whether an unknown point cloud belongs to a target normal category using only a few normal references. Existing train…
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…