3D Point Cloud Classification on ScanObjectNN-C 1.0 (test) benchmark leaderboard · SOTA2 Research

3D Point Cloud Classification on ScanObjectNN-C 1.0 (test)

44.62Accuracy (Uniform Noise)SVWA

Evaluation Results

Method	Links
SVWA2026.06		44.62	60.94	25.17	38.72	46.7	52.6	55.56	72.05	72.4	52.6	44.44	71.18	53.99	9.38	11.46	47.45
MAMVI2026.06		43.06	60.07	22.92	41.15	45.49	56.77	61.81	74.83	74.83	56.77	48.79	77.26	63.72	8.33	10.59	49.76
SAR2026.06		41.65	38.73	18.24	46.47	39.24	57.14	62.65	66.61	65.58	60.41	52.32	68.16	62.48	8.95	9.47	47.26
PG-SP2026.06		41.48	55.59	22.89	38.9	42.17	56.8	62.31	76.08	76.42	59.04	49.74	76.76	62.48	7.57	8.78	49.13
PG-SF2026.06		40.96	54.76	21.86	36.49	39.59	55.25	58.35	75.56	74.04	56.8	48.71	75.56	58.69	7.06	9.47	47.54
PL2026.06		39.76	36.83	19.1	43.55	37.87	57.14	62.31	66.27	66.27	60.59	49.74	67.3	61.79	8.26	9.12	46.51
TENT2026.06		39.24	34.42	17.04	44.75	34.77	58	59.04	66.95	66.95	60.24	50.26	67.64	61.27	7.06	9.12	45.97
T3A2026.06		37.5	46.01	18.92	37.33	37.67	50.69	52.26	63.72	65.97	50.35	46.88	64.41	54.17	9.72	8.68	42.95
DUA2026.06		30.5	40.1	10.2	23.6	29.9	43.7	46.1	68.3	66.3	48.5	38.9	68.7	48.4	8.6	8.1	38.66
TTT-Rot2026.06		30.2	34.1	16.2	22.6	22.6	32.4	32.1	45.5	45	34.5	29.3	47.8	36.2	7.1	8.1	29.58
MATE2026.06		27.5	29.4	14.3	22.2	25.6	40.8	42	73.7	63.2	45.1	35.3	73.3	45.3	7.1	9.3	36.9
SMART-PC2026.06		27.5	39.1	19.3	21.5	29.8	44.2	48.9	68.3	60.2	49.4	45.4	70.1	49.1	8.4	12.2	39.6
SHOT2026.06		25.82	34.25	13.08	54.04	32.53	57.49	58.86	66.44	66.61	54.73	46.99	65.92	63.34	6.02	8.26	44.57
Source Only2026.06		21.69	18.76	16.7	18.42	22.2	45.96	46.99	71.95	69.36	48.88	35.63	72.98	49.4	6.71	8.78	36.96
BFTT3D2026.06		16.35	14.97	14.29	17.04	13.43	38.9	42	69.71	70.74	41.14	28.92	69.19	43.2	6.54	8.61	33
LAME2026.06		14.46	12.56	10.33	15.83	12.91	48.88	55.59	58.35	61.1	52.32	35.8	58.35	53.36	9.12	9.47	34.91