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
1MC4ADO-AUROC0.91—Unverified
2PASDFO-AUROC0.9—Unverified
3MC3D-ADO-AUROC0.84—Unverified
4PO3ADO-AUROC0.84—Unverified
5DUS-NetO-AUROC0.8—Unverified
6R3D-ADO-AUROC0.75—Unverified
7ISMPO-AUROC0.71—Unverified
8IMRNetO-AUROC0.66—Unverified