Semantic Segmentation on MFNet Dataset (test) benchmark leaderboard · SOTA2 Research

Semantic Segmentation on MFNet Dataset (test)

97.97Background IoURTFNet-152

Evaluation Results

Method	Links
RTFNet-1522019.09		97.97	87.1	67	61	41.61	23.6	3	32	49.47	51.41
RTFNet-502019.09		97.89	83.88	66.76	60.1	43.28	12.6	5.51	26.6	56.84	50.38
Ours: Full2019.09		97.01	76.84	52.57	55.29	29.57	25.09	15.1	39.36	44.98	48.42
ERFNet2019.09		96.94	73.84	64.65	51.28	37.73	18.33	3.62	40.23	45.92	48.06
UNet*2019.09		96.9	66.2	60.5	46.2	41.6	17.9	1.8	30.6	44.2	45.1
Ours: Naïve2019.09		96.9	72.98	62	51.66	38.72	20.11	1.5	36.91	44.21	47
Ours: RGB Stream2019.09		96.78	76.73	48.73	55.32	29.17	27.85	15.25	35.8	42.64	47.76
MFNet2019.09		96.35	61.54	55.3	43.41	22.31	7.97	0.28	20.88	24.71	36.97
UNet*2019.09		96.2	65.2	42.6	47.8	27.8	20.8	0	35.8	31	40.8
Fast-SCNN2019.09		96.16	42.63	51.41	47.35	24.56	10.87	0	22.3	34.62	32.83
ERFNet2019.09		95.89	70.51	41.76	50.29	26.27	20.7	6.38	36.43	30.69	41.99
Fast-SCNN2019.09		94.77	40.75	23.34	22.37	23.58	9.45	1.66	22.42	21.65	28.88
MAVNet2019.09		88.43	37.54	39.75	15.21	8.5	2.4	0	4	4.4	22.26
MAVNet2019.09		82.64	41.56	13.04	28.78	5.3	2.9	0.19	5.6	1.15	20.14