Semantic Segmentation on Potsdam (mIoU, mACC) benchmark leaderboard · SOTA2 Research

Semantic Segmentation on Potsdam (mIoU, mACC)

45.91mIoUDR-Seg

Evaluation Results

Method	Links
DR-Seg2026.04		45.91	60.14
DR-Seg2026.04		41.55	57.69
GSNet2026.04		37.85	52.35
SAN2026.04		37.25	46.28
RSKT-Seg2026.04		37.14	53.75
OVRS2026.04		36.44	50.17
Cat-Seg2026.04		35.75	49.03
RSKT-Seg2026.04		34.53	50.71
SAN2026.04		30.3	44.98
DR-Seg2026.04		29.67	52.9
SED2026.04		29.35	37.95
RSKT-Seg2026.04		28.57	51.69
GSNet2026.04		28.5	52
SCAN2026.04		28.32	52.47
OVRS2026.04		27.47	42.07
SCAN2026.04		27.45	39.22
Cat-Seg2026.04		26.79	44.72
GSNet2026.04		26.46	43.2
OVRS2026.04		26.39	50.15
SAN2026.04		24.72	56.54
Cat-Seg2026.04		23.9	49.49
RSKT-Seg2026.04		20.28	46.71
SCAN2026.04		20.22	34.7
SED2026.04		19.47	33.4
DR-Seg2026.04		19.4	41.24
SCAN2026.04		18.25	33.17
OVRS2026.04		15.57	38.94
Cat-Seg2026.04		15.23	37.17
GSNet2026.04		15.12	36.16
SAN2026.04		14.82	34.84
SED2026.04		11.85	23.87
SED2026.04		5.78	17.52