SOTAVerified

3D Anomaly Detection

3D-only Anomaly Detection. Structures out of normal distribution are detected from the 3D-only point cloud.

Papers

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Showing 1–10 of 36 papers

TitleStatusHype
Towards High-Resolution 3D Anomaly Detection: A Scalable Dataset and Real-Time Framework for Subtle Industrial DefectsCode2
Taming Anomalies with Down-Up Sampling Networks: Group Center Preserving Reconstruction for 3D Anomaly Detection—0
SiM3D: Single-instance Multiview Multimodal and Multisetup 3D Anomaly Detection Benchmark—0
Bridging 3D Anomaly Localization and Repair via High-Quality Continuous Geometric RepresentationCode0
Mentor3AD: Feature Reconstruction-based 3D Anomaly Detection via Multi-modality Mentor Learning—0
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly DetectionCode0
Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving—0
MC3D-AD: A Unified Geometry-aware Reconstruction Model for Multi-category 3D Anomaly Detection—0
Robust Distribution Alignment for Industrial Anomaly Detection under Distribution Shift—0
Fence Theorem: Preprocessing is Dual-Objective Semantic Structure Isolator in 3D Anomaly Detection—0
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All datasetsReal 3D-ADAnomaly-ShapeNetAnomaly-ShapeNet10

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DUS-NetMean Performance of P. and O. 0.82—Unverified
2MC4ADMean Performance of P. and O. 0.81—Unverified
3ISMPMean Performance of P. and O. 0.8—Unverified
4MC3D-ADMean Performance of P. and O. 0.78—Unverified
5PASDFMean Performance of P. and O. 0.77—Unverified
6PO3ADMean Performance of P. and O. 0.77—Unverified
7Group3ADMean Performance of P. and O. 0.74—Unverified
8PointADMean Performance of P. and O. 0.74—Unverified
9IMRNetMean Performance of P. and O. 0.73—Unverified
10GLFMMean Performance of P. and O. 0.72—Unverified