Image Classification on Red Mini-ImageNet (test) (Noise Robustness) benchmark leaderboard · SOTA2 Research

Image Classification on Red Mini-ImageNet (test) (Noise Robustness)

61.44Accuracy (Noise 0.2)Ours (CLIPCleaner + MixFix)

Evaluation Results

Method	Links
Ours (CLIPCleaner + MixFix)2024.08		61.44	58.42	53.18	43.82
GNL - p(Y\|X) ensemble2023.08		58.46	53.38	48.92	40.68
InstanceGM2024.08		58.38	52.24	47.96	39.62
GNL - p(X\|Y) ensemble2023.08		57.56	52.68	47.12	39.54
GNL - p(Y\|X)2023.08		54.53	50.23	45.12	35.78
GNL - p(X\|Y)2023.08		53.34	49.56	44.08	34.7
FaMUS2023.08		51.42	48.06	45.1	35.5
FaMUS2024.08		51.42	48.06	45.1	35.5
MentorMix2023.08		51.02	47.14	43.8	33.46
MentorMix2024.08		51.02	47.14	43.8	33.46
DivideMix2023.08		50.96	46.72	43.14	34.5
DivideMix2024.08		50.96	46.72	43.14	34.5
Mixup2023.08		49.1	46.4	40.58	33.58
Mixup2024.08		49.1	46.4	40.58	33.58
CE2023.08		47.36	42.7	37.3	29.76
CE2024.08		47.36	42.7	37.3	29.76