SOTAVerified|Agents Browse Leaderboard About Blog

3D Anomaly Detection

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

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 26–36 of 36 papers

Title	Date	Tasks	Status	Hype
Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network	Nov 25, 2023	3D Anomaly DetectionAnomaly Detection	CodeCode Available	1
Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead	Nov 5, 2023	3D Anomaly DetectionAnomaly Detection	CodeCode Available	1
Real3D-AD: A Dataset of Point Cloud Anomaly Detection	Sep 23, 2023	3D Anomaly DetectionAnomaly Detection	CodeCode Available	1
EasyNet: An Easy Network for 3D Industrial Anomaly Detection	Jul 26, 2023	3D Anomaly DetectionAnomaly Detection	—Unverified	0
Multimodal Industrial Anomaly Detection via Hybrid Fusion	Mar 1, 2023	3D Anomaly DetectionAnomaly Detection	CodeCode Available	2
Shape-Guided: Shape-Guided Dual-Memory Learning for 3D Anomaly Detection	Jan 27, 2023	3D Anomaly Detection3D Anomaly Detection and Segmentation	CodeCode Available	1
Teacher-Student Network for 3D Point Cloud Anomaly Detection with Few Normal Samples	Oct 31, 2022	3D Anomaly DetectionAnomaly Detection	—Unverified	0
Asymmetric Student-Teacher Networks for Industrial Anomaly Detection	Oct 14, 2022	3D Anomaly DetectionAnomaly Detection	CodeCode Available	1
Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection	Mar 10, 2022	3D Anomaly Detection3D Anomaly Detection and Segmentation	CodeCode Available	1
Anomaly Detection in 3D Point Clouds using Deep Geometric Descriptors	Feb 23, 2022	3D Anomaly Detection3D Anomaly Detection and Segmentation	—Unverified	0
Towards Total Recall in Industrial Anomaly Detection	Jun 15, 2021	3D Anomaly DetectionAnomaly Classification	CodeCode Available	2

Show:10 25 50

← PrevPage 2 of 2Next →

All datasets Real 3D-AD Anomaly-ShapeNet Anomaly-ShapeNet10

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	DUS-Net	Mean Performance of P. and O.	0.82	—	Unverified
2	MC4AD	Mean Performance of P. and O.	0.81	—	Unverified
3	ISMP	Mean Performance of P. and O.	0.8	—	Unverified
4	MC3D-AD	Mean Performance of P. and O.	0.78	—	Unverified
5	PASDF	Mean Performance of P. and O.	0.77	—	Unverified
6	PO3AD	Mean Performance of P. and O.	0.77	—	Unverified
7	Group3AD	Mean Performance of P. and O.	0.74	—	Unverified
8	PointAD	Mean Performance of P. and O.	0.74	—	Unverified
9	IMRNet	Mean Performance of P. and O.	0.73	—	Unverified
10	GLFM	Mean Performance of P. and O.	0.72	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MC4AD	O-AUROC	0.91	—	Unverified
2	PASDF	O-AUROC	0.9	—	Unverified
3	MC3D-AD	O-AUROC	0.84	—	Unverified
4	PO3AD	O-AUROC	0.84	—	Unverified
5	DUS-Net	O-AUROC	0.8	—	Unverified
6	R3D-AD	O-AUROC	0.75	—	Unverified
7	ISMP	O-AUROC	0.71	—	Unverified
8	IMRNet	O-AUROC	0.66	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MC4AD	O-AUROC	0.89	—	Unverified
2	PatchCore (FPFH)	O-AUROC	0.88	—	Unverified
3	BTF (FPFH)	O-AUROC	0.63	—	Unverified
4	M3DM	O-AUROC	0.57	—	Unverified
5	PatchCore (PointMAE)	O-AUROC	0.57	—	Unverified
6	Reg3D-AD	O-AUROC	0.53	—	Unverified
7	BTF (Raw)	O-AUROC	0.5	—	Unverified