Robust Image Classification on CIFAR-10 (test) (Symmetric & Asymmetric Noise) benchmark leaderboard · SOTA2 Research

Robust Image Classification on CIFAR-10 (test) (Symmetric & Asymmetric Noise)

96.75Accuracy (Symmetric Noise, η=0.2)Ours (Modified Model)

Evaluation Results

Method	Links
Ours (Modified Model)2022.10		96.75	—	—	—	94.98	—	—	96.42	96.16	93.93
ContrastToDivide2022.10		96.4	—	—	—	94.4	—	—	93.5	95.3	93.6
AugDesc2022.10		96.3	—	—	—	93.8	—	—	94.6	95.4	91.9
PropMix2022.10		96.09	—	—	—	93.77	—	—	94.64	95.53	93.2
Ours (Modified Model)2022.10		95.99	—	—	—	94.48	—	—	95.85	95.59	93.52
ELR2022.10		95.8	—	—	—	93.3	—	—	93	94.8	78.7
DivideMix2022.10		95.7	—	—	—	92.9	—	—	92.1	94.4	75.4
Ours (Normal Model)2022.10		95.47	—	—	—	94.9	—	—	95.14	95.39	92.32
Ours (Normal Model)2022.10		95.04	—	—	—	94.51	—	—	94.91	95.13	91.72
FasTEN2021.11		91.94	—	90.07	86.78	79.52	92.29	—	90.43	—	—
MSLC2021.11		90.94	—	88.36	83.93	64.9	91.45	—	89.26	—	—
MLOC2021.11		90.5	—	87.2	81.95	54.64	91.15	—	89.35	—	—
Deep kNN2021.11		90.02	—	87.27	82.8	68.3	89.97	—	84.56	—	—
MW-Net2021.11		89.76	—	86.52	81.68	56.56	91.31	—	88.69	—	—
MLaC2021.11		89.75	—	86.63	82.2	71.94	91.45	—	90.26	—	—
GLC2021.11		89.66	—	85.3	80.34	67.44	91.56	—	89.76	—	—
L2RW2021.11		88.26	—	83.76	74.54	42.6	88.79	—	85.86	—	—
SL2019.08		87.63	89.28	85.34	80.07	53.81	88.24	85.36	80.64	—	—
Forward2019.08		85.83	89.39	81.37	73.59	47.1	87.68	84.86	85.73	—	—
GCE2019.08		84.86	86.76	82.42	75.2	40.81	84.61	82.11	75.32	—	—
Bootstrap2019.08		83.95	88.77	79.97	71.65	41.44	86.57	86.86	79.76	—	—
LSR2019.08		83.49	88.57	78.41	67.38	36.3	85.38	84.86	77.88	—	—
CE2019.08		82.96	89.26	78.7	66.62	34.8	85.98	82.89	78.51	—	—
Cross-Entropy2022.10		82.7	—	—	—	26.1	—	—	72.3	57.9	16.8
D2L2019.08		81.13	86.66	76.8	60.67	19.83	82.72	80.41	73.33	—	—