Semantic Segmentation on Mean over 8 Remote Sensing Datasets benchmark leaderboard · SOTA2 Research

Semantic Segmentation on Mean over 8 Remote Sensing Datasets

49.01Mean mIoUDR-Seg

Evaluation Results

Method	Links
DR-Seg2026.04		49.01	64.9
RSKT-Seg2026.04		46.18	62.35
DR-Seg2026.04		45	60.42
GSNet2026.04		44.56	60.89
OVRS2026.04		44.39	60.24
Cat-Seg2026.04		44.23	57.58
RSKT-Seg2026.04		43.9	59.51
SAN2026.04		41.8	53.81
SED2026.04		40.18	53.13
GSNet2026.04		40.08	55.87
OVRS2026.04		39.57	54.51
DR-Seg2026.04		37.84	60.14
SAN2026.04		36.96	51.36
RSKT-Seg2026.04		36.76	57.91
Cat-Seg2026.04		36.62	52.21
OVRS2026.04		36.18	56.05
GSNet2026.04		35.71	56.48
DR-Seg2026.04		33.89	55.3
Cat-Seg2026.04		33.11	52.8
SED2026.04		32.88	47.91
SCAN2026.04		30.78	45.87
RSKT-Seg2026.04		30.03	52.73
SAN2026.04		30.01	49.98
SED2026.04		28.99	44.01
GSNet2026.04		27.87	47.14
OVRS2026.04		27.59	47.05
Cat-Seg2026.04		26.82	46.45
SCAN2026.04		25.43	41.19
SAN2026.04		25.04	41.65
SCAN2026.04		24.69	44.86
SED2026.04		24.05	38.97
SCAN2026.04		18.95	35.78