Semantic Segmentation on COCO-EA benchmark leaderboard · SOTA2 Research

Semantic Segmentation on COCO-EA

94mRDeepLabV3+

Evaluation Results

Method	Links
DeepLabV3+2026.03		94	—	—	—	—	—	—	22.07	20.67	19.64	21.45	20.8
PSPNet2026.03		93	—	—	—	—	—	—	22.18	20.89	19.75	21.44	20.87
OVSeg2026.03		92	49.64	48.4	47.27	46.22	42.7	41.27	—	—	—	—	—
GCNet2026.03		92	—	—	—	—	—	—	22.78	21.11	19.46	21.74	21.36
Segmenter2026.03		92	—	—	—	—	—	—	23.65	22.02	19.71	22.81	22.15
ODISE2026.03		92	—	—	—	—	—	—	23.45	21.59	20.07	22.7	21.93
Segmenter2026.03		91	46.93	46.38	45.28	42.64	41.75	39.39	—	—	—	—	—
CATSeg2026.03		91	50.99	50.62	49.2	48.33	44.56	42.8	—	—	—	—	—
Mask2Former2026.03		91	—	—	—	—	—	—	21.81	19.93	18.73	20.7	19.64
OVSeg2026.03		91	—	—	—	—	—	—	23.42	21.48	19.82	22.45	21.54
X-Decoder2026.03		90	50.12	49.15	47.46	44.5	43.85	41.96	—	—	—	—	—
SEEM2026.03		90	49.72	48.94	46.92	43.92	41.81	42.82	—	—	—	—	—
SegFormer2026.03		90	—	—	—	—	—	—	22.95	21.67	19.03	21.39	20.54
MaskFormer2026.03		90	—	—	—	—	—	—	22.79	21.02	19.47	21.77	19.98
X-Decoder2026.03		90	—	—	—	—	—	—	28.26	25.53	23.81	26.59	25.58
CATSeg2026.03		90	—	—	—	—	—	—	23.15	21.14	19.72	21.92	21.11
SEEM2026.03		90	—	—	—	—	—	—	27.38	25.45	22.98	25.62	24.86
ODISE2026.03		89	48.31	47.79	46.59	43.06	40.01	41.55	—	—	—	—	—
OCRNet2026.03		89	—	—	—	—	—	—	23.03	21.22	19.5	21.01	20.68
SegFormer2026.03		87	43.1	42.69	40.07	38.5	37.49	34.2	—	—	—	—	—
MaskFormer2026.03		87	43.66	43.07	41.23	39.27	36.52	33.41	—	—	—	—	—
DeepLabV32026.03		85	36.98	36.25	33.68	30.68	31.28	28.27	—	—	—	—	—
Mask2Former2026.03		85	45.77	45.06	41.64	38.6	38.52	34.54	—	—	—	—	—
PSPNet2026.03		84	36.2	35.54	32.8	29.62	30.25	27.23	—	—	—	—	—
OCRNet2026.03		82	40.55	39.74	37.69	33.94	30.04	29.16	—	—	—	—	—
GCNet2026.03		80	37.59	37	35.07	29.65	28.34	26.03	—	—	—	—	—