Anomaly Segmentation on MVTec-3D 1.0 (test) benchmark leaderboard · SOTA2 Research

Anomaly Segmentation on MVTec-3D 1.0 (test)

0.98BagelPADIM

Evaluation Results

Method	Links
PADIM2023.03		0.98	0.944	0.945	0.925	0.961	0.792	0.966	0.94	0.937	0.912	0.93	—
PatchCore + FPFH2023.03		0.976	0.969	0.979	0.973	0.933	0.888	0.975	0.981	0.95	0.971	0.959	—
FPFH2023.03		0.973	0.879	0.982	0.906	0.892	0.735	0.977	0.982	0.956	0.961	0.924	—
M3DM2023.03		0.97	0.971	0.979	0.95	0.941	0.932	0.977	0.971	0.971	0.975	0.961	—
M3DM2023.03		0.952	0.972	0.973	0.891	0.932	0.843	0.97	0.956	0.968	0.966	0.942	—
3D-ST2023.03		0.95	0.483	0.986	0.921	0.905	0.632	0.945	0.988	0.976	0.542	0.833	—
M3DM2023.03		0.943	0.818	0.977	0.882	0.881	0.743	0.958	0.974	0.95	0.929	0.906	—
PatchCore2023.03		0.901	0.949	0.928	0.877	0.892	0.563	0.904	0.932	0.908	0.906	0.876	—
CFlow2023.03		0.855	0.919	0.958	0.867	0.969	0.5	0.889	0.935	0.904	0.919	0.871	—
Voxel GAN2023.03		0.664	0.62	0.766	0.74	0.783	0.332	0.582	0.79	0.633	0.483	0.639	—
Voxel VM2023.03		0.51	0.331	0.413	0.715	0.68	0.279	0.3	0.507	0.611	0.366	0.471	—
Voxel AE2023.03		0.467	0.75	0.808	0.55	0.765	0.473	0.721	0.918	0.019	0.17	0.564	—
Voxel VM2023.03		0.453	0.343	0.521	0.697	0.68	0.284	0.349	0.634	0.616	0.346	0.492	—
Voxel GAN2023.03		0.44	0.453	0.875	0.755	0.782	0.378	0.392	0.639	0.775	0.389	0.583	—
Depth AE2023.03		0.432	0.158	0.808	0.491	0.841	0.406	0.262	0.216	0.716	0.478	0.481	—
Depth GAN2023.03		0.421	0.422	0.778	0.696	0.494	0.252	0.285	0.362	0.402	0.631	0.474	—
Depth VM2023.03		0.388	0.321	0.194	0.57	0.408	0.282	0.244	0.349	0.268	0.331	0.335	—
Depth VM2023.03		0.28	0.374	0.243	0.526	0.485	0.314	0.199	0.388	0.543	0.385	0.374	—
Voxel AE2023.03		0.26	0.341	0.581	0.351	0.502	0.234	0.351	0.658	0.015	0.185	0.348	—
Depth AE2023.03		0.147	0.069	0.293	0.217	0.207	0.181	0.164	0.066	0.545	0.142	0.203	—
Depth GAN2023.03		0.111	0.072	0.212	0.174	0.16	0.128	0.003	0.042	0.446	0.075	0.143	—