Motor Imagery Classification on BCI Competition IV-2b Dataset I (cross-subject) benchmark leaderboard · SOTA2 Research

Motor Imagery Classification on BCI Competition IV-2b Dataset I (cross-subject)

80.83Average AccuracyHCFT

Evaluation Results

Method	Links
HCFT2026.01		80.83	78.62	73.23	67.71	93.92	82.72	82.68	86.17	84.47	77.94	7.61	0.6165
SCNN2026.01		79.38	—	—	—	—	—	—	—	—	—	14.17	—
ConTraNet2026.01		76.57	72.92	72.94	63.75	83.51	82.7	80.69	84.44	77.37	70.83	6.97	—
Conformer2026.01		76.4	65.89	64.43	67.45	84.45	72.24	76.56	77.86	69.23	74.87	6.51	0.4521
CTNet2026.01		76.27	76.25	71.03	66.39	81.76	83.11	77.22	79.17	73.56	77.92	5.26	0.5252
MSHCNN2026.01		76.03	76.8	66.32	57.36	91.75	79.59	82.63	74.16	80.13	75.55	9.79	—
MSCFormer2026.01		75.25	76.11	71.18	62.36	81.35	81.08	74.72	78.89	76.18	75.42	5.8	0.5051
MSNN2026.01		75.02	74.72	65.29	57.63	91.21	74.72	85.55	72.91	76.57	76.66	9.88	—
EEGPT2026.01		74.7	72.22	69.71	61.53	78.78	81.08	70.42	83.89	83.82	70.83	7.61	0.4936
Hybrid EEGNet2026.01		73.72	71.53	65	58.75	84.86	78.78	77.5	77.92	73.68	75.41	7.82	—
EEGNet2026.01		73.45	66.15	71.08	72.01	56.48	80.24	78.78	85.03	79.54	71.74	8.64	0.4684
EEGCCT2026.01		73.26	68.75	59.6	59.9	89.21	73.44	75.39	76.3	75.76	77.73	9.21	0.4587
ConvNet2026.01		70.65	64.19	62.9	67.58	72.06	75.87	72.01	81.51	79.02	60.68	7.33	0.4134
Hybrid t-CViT2026.01		66.79	66.39	55.74	52.36	82.7	72.57	63.89	68.89	65.92	72.64	9.12	—
Hybrid s-CViT2026.01		64.44	68.47	56.91	50.42	81.08	60.68	61.67	62.22	70	68.47	8.81	—