AF3AD is a modular synthesis framework using center-conditioned parametric deformations in local PCA frames to create diverse pseudo-anomalies, improving unsupervised 3D anomaly detection on AnomalyShapeNet and Real3D-AD.
Clip3d-ad: Extending clip for 3d few-shot anomaly detection with multi-view images generation,
3 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
3
Pith papers citing it
1
external citations · external index
fields
cs.CV 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
VT-3DAD fuses visual deviation from few-shot references and semantic deviation from textual normal space to achieve SOTA cross-category 3D anomaly detection on ShapeNetPart.
MambaADv2 evolves Mamba state space models with hybrid blocks, frequency convolutions, and adaptive scanning for improved unsupervised anomaly detection.
citing papers explorer
-
Anomaly Factory 3D: A Modular Framework for Diverse Pseudo-Anomaly Synthesis in Unsupervised 3D Anomaly Detection
AF3AD is a modular synthesis framework using center-conditioned parametric deformations in local PCA frames to create diverse pseudo-anomalies, improving unsupervised 3D anomaly detection on AnomalyShapeNet and Real3D-AD.
-
VT-3DAD: Cross-Category 3D Anomaly Detection via Visual-Text Normal Space Alignment
VT-3DAD fuses visual deviation from few-shot references and semantic deviation from textual normal space to achieve SOTA cross-category 3D anomaly detection on ShapeNetPart.
-
MambaADv2: Evolving Duality-enhanced State Space Model for Unsupervised Anomaly Detection
MambaADv2 evolves Mamba state space models with hybrid blocks, frequency convolutions, and adaptive scanning for improved unsupervised anomaly detection.