Image Classification on Cross-Domain Classification Suite (12 datasets) (test) benchmark leaderboard · SOTA2 Research

Image Classification on Cross-Domain Classification Suite (12 datasets) (test)

49.89ChestX AccuracySL-MLP

Evaluation Results

Method	Links
SL-MLP2021.12		49.89	99.02	87.86	72.61	96.63	93.46	81.12	76.73	94.2	85.36	67.82	67.13	81.15
SelfSupCon†2021.12		48.08	99.06	87.88	72.71	96.97	89.62	81.67	69.66	90.88	69.12	69.95	81.51	79.7
SupCon2021.12		47.71	98.79	85.66	74.2	95.83	92.24	79.42	73.42	91.14	76.8	74.26	79.78	80.77
SL2021.12		45.45	96.8	84.02	66.22	95.07	83.69	75.4	64.14	91.66	74.51	75.16	81.53	81.68
SelfSupCon†2021.12		43.09	93.95	88.1	62.95	95.47	88.92	79.41	45.33	81.14	10.57	82.37	78.27	70.88
SL-MLP2021.12		42.34	94.48	89.64	63.9	95.3	90.2	77.98	46.66	83.13	17.32	80.19	78.82	71.66
SupCon2021.12		41.84	93.46	88.7	61.81	94.54	91.28	78.35	46.02	81.62	15.84	81.85	78.51	71.15
SupCon w/o MLP2021.12		41.72	93.52	84.95	58.09	95.15	88.23	78.95	45.68	80.63	14.39	82.25	77.96	70.12
SupCon w/o MLP2021.12		41.38	91.52	73.16	62.93	89.84	73.23	66.38	44.54	76.55	55.21	61.45	68.54	67.06
SL2021.12		40.86	94.31	86.95	62.12	94.05	88.94	78.22	46.16	80.32	14.17	82.16	78.28	70.54
SL-MLP2021.12		26.89	93.45	59.08	83.04	87.16	96.88	50.77	95.73	89	89.84	41.96	46.76	71.71
SupCon2021.12		26.18	94.09	59.36	85.02	87.97	96.55	51.02	94.49	89.01	89.75	41.67	43.48	71.55
SL2021.12		25.64	89.07	54.32	78.58	82.96	93.14	46.14	92.82	84.17	87.06	38.03	41.22	67.76
SupCon w/o MLP2021.12		23.62	75.64	49.34	73.04	73.9	82.16	38.1	67.87	75.18	81.01	34.92	35.16	59.16