Point Cloud Classification Robustness on ModelNet40 (test) benchmark leaderboard · SOTA2 Research

Point Cloud Classification Robustness on ModelNet40 (test)

0.59mCE (Error Rate)DGCNN + WOLFMix

Evaluation Results

Method	Links
DGCNN + WOLFMix2024.01		0.59	0.989	0.715	0.698	0.575	0.285	0.415	0.451
DGCNN + RSMix2024.01		0.745	1.319	0.873	0.653	0.589	0.281	0.629	0.87
PointMLS2024.01		0.784	1.181	0.652	0.565	0.913	0.522	0.756	0.902
DGCNN + PointWOLF2024.01		0.814	0.926	0.864	0.988	0.874	0.807	0.764	0.479
RPC2024.01		0.863	0.84	0.892	0.492	0.797	0.929	1.011	1.079
GDANet2024.01		0.892	0.83	0.839	0.794	0.894	0.871	1.036	0.981
PCT2024.01		0.925	0.872	0.87	0.528	1	0.78	1.385	1.042
CurveNet2024.01		0.927	0.872	0.725	0.71	1.024	1.346	1	0.809
DGCNN2024.01		1	1	1	1	1	1	1	1
PointNet2 + PointMixUp2024.01		1.028	1.67	0.712	0.802	1.812	0.458	0.615	1.13
SimpleView2024.01		1.047	0.872	0.715	1.242	1.357	0.983	0.844	1.316
DGCNN + OcCo2024.01		1.047	1.606	0.652	0.903	1.039	1.444	0.847	0.837
PointNet22024.01		1.072	0.872	1.177	0.641	1.802	0.614	0.993	1.405
PAConv2024.01		1.104	0.904	1.465	1	1.005	1.085	1.298	0.967
RSCNN2024.01		1.13	1.074	1.171	0.806	1.517	0.712	1.153	1.479
Point-BERT2024.01		1.248	0.936	1.259	0.69	1.15	1.932	1.44	1.326
PointNet2024.01		1.422	1.266	0.642	0.5	1.072	2.98	1.593	1.902