Place Categorization on Multi-modal Panoramic 3D Outdoor (MPO) (test) benchmark leaderboard · SOTA2 Research

Place Categorization on Multi-modal Panoramic 3D Outdoor (MPO) (test)

94.59Coast AccuracyAdaptive Fusion

Evaluation Results

Method	Links
Adaptive Fusion2026.03		94.59	98.2	99.77	94.85	99.19	99.37	97.62
Softmax Average2026.03		94.27	98.38	99.58	94.91	99.12	99.56	97.87
Late Fusion2026.03		93.49	97.57	99.25	94.23	98.39	98.88	97.19
Early Fusion2026.03		93.37	98.09	99.44	94.71	98.21	97.15	97.02
VGG2026.03		92.73	97.26	99.94	94.23	98.35	99.2	97.18
VGG + RWMP + HCC2026.03		91.83	98.2	91.45	95.16	97.99	98.27	95.92
VGG + RWMP + HCC2026.03		91.83	98.2	91.45	95.16	97.99	98.27	95.92
VGG + RWMP2026.03		91.13	97.63	93.29	94.67	97.93	97.37	95.74
VGG + HCC2026.03		91	98.38	94.39	94.13	97.58	95.01	95.45
VGG2026.03		90.58	97.99	92.37	93.89	96.4	95.06	94.75
ResNet2026.03		90.3	96.62	94.6	93.63	96.13	96.09	94.83
LBP + RBF-SVM2026.03		76.66	95.67	80.18	92.74	88.44	79.53	86.19
GIST + RBF-SVM2026.03		68.85	91.65	74.07	81.73	79.88	75.03	79.15