Image Classification on AG-Fashion-MNIST (test) (Transformation Robustness) benchmark leaderboard · SOTA2 Research

Image Classification on AG-Fashion-MNIST (test) (Transformation Robustness)

44.48Top-1 Accuracy (I=4 Hor)ICPNet

Updated 1mo ago

Evaluation Results

Method	Links
ICPNet2025.08		44.48	42.69	42.25	47.81	68.53	77.15	77.36	73.83	48.04	46.39	42.9	50.42	52.95	68.51	69.65	38.75	34.75	23.95	18.93	13.95	36.5	59.34	61.03	34.05
ConvNeXt-B2025.08		19.3	10.08	10.21	21.25	10.14	9.53	10.16	11.27	12.88	9.37	9.93	16.67	14.38	12.11	10.18	10.92	10.92	20.52	10.88	12.64	10.03	12.91	10.89	7.03
MambaOut-B2025.08		15.97	11.2	12.58	15.28	15.93	10.04	16.07	16.44	11.4	11.05	11.09	19.64	13.44	15.53	19.12	13.97	20.82	17.07	17.29	23.33	11.59	15.06	19.84	6.49
Swin-B2025.08		12.65	9.43	8.22	4.34	5.18	12.9	12.63	10.14	11.14	12.97	17.15	3.6	2.21	10.14	12.97	17.66	6.71	12.54	6.22	9.99	6.73	10.08	10.14	10.15
ResNet1012025.08		11.04	10.14	10.14	16.23	13.92	10.04	17.92	13.31	10.67	11.29	11.01	8.65	14.39	10.74	6.45	10.86	27.32	6.71	6.71	9.7	10.14	6.71	6.71	15.49
ResNet182025.08		10.34	10.45	10.46	16.21	15.66	17.74	11.53	24.2	10.69	12.49	12.63	18.29	9.85	10.66	10.86	9.28	54.74	6.71	6.75	38.25	10.14	6.77	6.77	7.28
ViT-L-162025.08		10.24	8.58	10.04	8	10.23	9.66	10.14	11.46	10.08	9.8	11.77	3.53	7.69	6.71	10.89	10.53	12.98	12.33	10.13	10.74	10.14	10.14	10.06	10.53
VGG162025.08		10.13	10.14	10.14	10.22	15.85	10.14	10.14	14.75	21.02	10.14	13.29	20.64	26.07	10.04	15.59	22.8	28.93	11.25	18.29	24.55	27.94	14.86	17.29	18.3