Image Classification on Flowers, CUB, Cars, CIFAR-10, CIFAR-100, Food, iNat (Average) benchmark leaderboard · SOTA2 Research

Image Classification on Flowers, CUB, Cars, CIFAR-10, CIFAR-100, Food, iNat (Average)

97.2Accuracy (Flowers)FRONT+

Evaluation Results

Method	Links
FRONT+2026.03		97.2	78.2	89.4	97.4	84	86.1	68.1	85.8
WAVE2026.03		96.9	78.1	89.4	97.4	83.2	85.5	67.6	85.4
Auto-LG2026.03		96.4	75.1	88.2	97.3	81	84.6	67	84.2
Direct FT2026.03		96.4	77	89.4	97.5	82.8	85.6	69.3	85.4
LiGO2026.03		95.9	74.8	87.9	96.9	81.3	84	66.1	83.8
Direct FT2026.03		95.4	75.1	86.5	96.6	80.2	84	66.9	83.5
FRONT+2026.03		95.1	75.2	86.1	96.6	80.8	83.9	65.4	83.3
WAVE2026.03		94.9	74.8	84.4	96.6	80.7	83.8	65.2	82.9
FRONT2026.03		94.5	74.1	87.4	97.2	81.8	85.2	66.6	83.9
LiGO2026.03		94.2	71.8	83.9	95.6	78.5	82.1	61.6	81.1
Share Init2026.03		94.1	72.4	87.2	96.5	78.5	83	63	82.1
TLEG2026.03		93.7	72.6	87.2	97.2	80.2	84.9	66.5	83.2
Auto-LG2026.03		93.5	71.4	83.5	96.4	77.1	81.7	62.5	80.9
FRONT2026.03		92.9	70.5	82.3	95.9	78.7	83.7	63.7	81.1
Share Init2026.03		92.4	70.1	82.1	96	77.2	81.2	63.2	80.3
TLEG2026.03		91	69.5	78.2	96.1	77	82	63.4	79.6
Heur-LG2026.03		69.1	48	51.2	95.1	72.8	76.8	59.3	67.5
Cluster-LG2026.03		65.5	45.4	46.3	95.4	74.6	78.4	60.4	66.6
Heur-LG2026.03		64.7	44.6	37.7	94	71.1	74.7	57.4	63.5
Cluster-LG2026.03		62.8	44.8	36.9	94.1	74.5	78.6	56.4	64
Wt Select2026.03		58.3	33.1	28.1	94.1	68.1	69	54.2	57.8
Mimetic2026.03		57.4	39.6	34.2	91.6	65.7	67.1	52.2	58.3
He-Init2026.03		57.2	27.3	23.8	94	66.5	70.6	54	56.2
Wt Select2026.03		55	34.4	21.7	92.5	67	67.4	51.2	55.6
He-Init2026.03		53.9	26.1	19.9	92.4	68.3	68.4	52.3	54.5
GHN-32026.03		52.7	45.2	30.6	93.9	72.7	76.2	55.5	61
Mimetic2026.03		52.1	35	20.5	88.9	63.4	66.9	49	53.7
GHN-32026.03		50	41.1	23.2	92.5	70.1	76.2	51.7	57.8