Semantic Segmentation on Dark Zurich 1.0 (test) benchmark leaderboard · SOTA2 Research

Semantic Segmentation on Dark Zurich 1.0 (test)

90.4Road IoUDANNet

Evaluation Results

Method	Links
DANNet2021.04		90.4	60.1	71	33.6	22.9	30.6	34.3	33.7	70.5	31.8	80.2	45.7	41.6	67.4	16.8	0	73	31.6	22.9	45.2
DANNet2021.04		90	54	74.8	41	21.1	25	26.8	30.2	72	26.2	84	47	33.9	68.2	19	0.3	66.4	38.3	23.6	44.3
DANNet2021.04		88.6	53.4	69.8	34	20	25	31.5	35.9	69.5	32.2	82.3	44.2	43.7	54.1	22	0.1	40.9	36	24.1	42.5
AdaptSegNet2021.04		86.1	44.2	55.1	22.2	4.8	21.1	5.6	16.7	37.2	8.4	1.2	35.9	26.7	68.2	45.1	0	50.1	33.9	15.6	30.4
ADVENT2021.04		85.8	37.9	55.5	27.7	14.5	23.1	14	21.1	32.1	8.7	2	39.9	16.6	64	13.8	0	58.8	28.5	20.7	29.7
BDL2021.04		85.3	41.1	61.9	32.7	17.4	20.6	11.4	21.3	29.4	8.9	1.1	37.4	22.1	63.2	28.2	0	47.7	39.4	15.7	30.8
GCMA2021.04		81.7	46.9	58.8	22	20	41.2	40.5	41.6	64.8	31	32.1	53.5	47.5	75.5	39.2	0	49.6	30.7	21	42
MGCDA2021.04		80.3	49.3	66.2	7.8	11	41.4	38.9	39	64.1	18	55.8	52.1	53.5	74.7	66	0	37.5	29.1	22.7	42.5
DeepLab-v22021.04		79	21.8	53	13.3	11.2	22.5	20.2	22.1	43.5	10.4	18	37.4	33.8	64.1	6.4	0	52.3	30.4	7.4	28.8
PSPNet2021.04		78.2	19	51.2	15.5	10.6	30.3	28.9	22	56.7	13.3	20.8	38.2	21.8	52.1	1.6	0	53.2	23.2	10.7	28.8
DMAda2021.04		75.5	29.1	48.6	21.3	14.3	34.3	36.8	29.9	49.4	13.8	0.4	43.3	50.2	69.4	18.4	0	27.6	34.9	11.9	32.1
RefineNet2021.04		68.8	23.2	46.8	20.8	12.6	29.8	30.4	26.9	43.1	14.3	0.3	36.9	49.7	63.6	6.8	0.2	24	33.6	9.3	28.5