Table 17: Results: Mapillary Vistas. Red: the best for each metric. Green: the worst for each metric.
Method	Backbone	mIoU1	mIoU1q	mIoU1b	mIoU1
mIoUC	mIoUCq	mIoUC5	mIoUC1
mIoUK	mIoUKq	mIoUK5	mIoUK1
mIoUD	mAcc	Acc
DeepLabV3+	ResNet101	62.47 ± 0.04	56.01 ± 0.04	44.61 ± 0.15	38.47 ± 0.21
46.23 ± 0.12	27.17 ± 0.07	3.06 ± 0.02	0.00 ± 0.00
45.25 ± 0.07	25.12 ± 0.04	2.54 ± 0.01	0.00 ± 0.00
47.76 ± 0.22	60.20 ± 0.27	91.36 ± 0.03
DeepLabV3+	ResNet50	60.61 ± 0.03	53.99 ± 0.05	42.58 ± 0.12	36.67 ± 0.12
43.31 ± 0.03	25.10 ± 0.03	2.95 ± 0.00	0.00 ± 0.00
42.52 ± 0.02	23.22 ± 0.03	2.48 ± 0.01	0.00 ± 0.00
44.30 ± 0.13	56.03 ± 0.14	90.76 ± 0.03
DeepLabV3+	ResNet34	58.35 ± 0.05	51.47 ± 0.05	39.78 ± 0.17	33.99 ± 0.54
38.16 ± 0.05	22.13 ± 0.07	2.56 ± 0.02	0.00 ± 0.00
37.09 ± 0.01	20.25 ± 0.07	2.26 ± 0.03	0.00 ± 0.00
38.74 ± 0.09	49.59 ± 0.14	90.22 ± 0.03
DeepLabV3+	ResNet18	56.55 ± 0.08	49.56 ± 0.09	37.75 ± 0.23	31.94 ± 0.33
36.00 ± 0.10	20.72 ± 0.08	2.41 ± 0.04	0.00 ± 0.00
35.03 ± 0.08	18.93 ± 0.06	2.13 ± 0.03	0.00 ± 0.00
36.58 ± 0.26	47.09 ± 0.30	89.63 ± 0.08
DeepLabV3+	EfficientNetB0	58.28 ± 0.06	51.44 ± 0.09	39.96 ± 0.12	35.18 ± 0.37
38.17 ± 0.15	22.25 ± 0.06	2.72 ± 0.03	0.00 ± 0.00
37.11 ± 0.13	20.38 ± 0.03	2.37 ± 0.04	0.00 ± 0.00
39.89 ± 0.39	50.43 ± 0.34	90.64 ± 0.06
DeepLabV3+	MobileNetV2	55.46 ± 0.04	48.50 ± 0.05	36.78 ± 0.15	31.03 ± 0.33
34.97 ± 0.13	19.87 ± 0.10	2.29 ± 0.01	0.00 ± 0.00
33.95 ± 0.11	18.14 ± 0.09	2.07 ± 0.02	0.00 ± 0.00
35.59 ± 0.05	45.60 ± 0.09	89.32 ± 0.03
DeepLabV3+	MobileViTV2	58.28 ± 0.02	51.47 ± 0.04	40.05 ± 0.08	34.97 ± 0.15
38.22 ± 0.03	22.32 ± 0.02	2.75 ± 0.02	0.00 ± 0.00
37.21 ± 0.01	20.49 ± 0.02	2.36 ± 0.01	0.00 ± 0.00
40.40 ± 0.12	50.41 ± 0.28	90.57 ± 0.01
UPerNet	ResNet101	61.68 ± 0.08	55.19 ± 0.06	43.86 ± 0.12	37.29 ± 0.22
46.05 ± 0.08	26.60 ± 0.04	3.01 ± 0.02	0.00 ± 0.00
45.15 ± 0.07	24.66 ± 0.01	2.47 ± 0.01	0.00 ± 0.00
48.15 ± 0.14	60.10 ± 0.34	91.20 ± 0.08
UPerNet	ConvNeXt	65.26 ± 0.01	59.12 ± 0.03	48.55 ± 0.07	42.90 ± 0.26
51.95 ± 0.04	30.91 ± 0.06	3.53 ± 0.02	0.00 ± 0.00
50.88 ± 0.02	28.68 ± 0.02	2.90 ± 0.01	0.00 ± 0.00
55.68 ± 0.12	67.63 ± 0.14	92.41 ± 0.04
UPerNet	MiTB4	64.48 ± 0.01	58.29 ± 0.02	47.66 ± 0.15	42.59 ± 0.57
50.08 ± 0.10	29.69 ± 0.02	3.48 ± 0.03	0.33 ± 0.47
49.11 ± 0.10	27.56 ± 0.01	2.83 ± 0.04	0.00 ± 0.00
54.22 ± 0.09	66.05 ± 0.11	92.41 ± 0.01
SegFormer	MiTB4	64.17 ± 0.02	57.97 ± 0.02	47.43 ± 0.02	42.50 ± 0.27
50.05 ± 0.05	29.59 ± 0.02	3.49 ± 0.08	0.33 ± 0.47
49.02 ± 0.08	27.45 ± 0.06	2.87 ± 0.08	0.33 ± 0.47
54.10 ± 0.04	65.96 ± 0.13	92.38 ± 0.03
SegFormer	MiTB2	62.15 ± 0.03	55.83 ± 0.01	45.15 ± 0.12	39.94 ± 0.14
46.70 ± 0.07	27.18 ± 0.06	3.15 ± 0.04	0.00 ± 0.00
45.75 ± 0.04	25.18 ± 0.05	2.63 ± 0.02	0.00 ± 0.00
51.02 ± 0.13	62.55 ± 0.24	91.91 ± 0.03
DeepLabV3	ResNet101	62.33 ± 0.03	55.94 ± 0.03	44.82 ± 0.05	38.66 ± 0.29
47.13 ± 0.02	27.44 ± 0.01	3.06 ± 0.02	0.00 ± 0.00
46.00 ± 0.08	25.26 ± 0.04	2.55 ± 0.01	0.00 ± 0.00
49.32 ± 0.33	61.35 ± 0.27	91.44 ± 0.03
PSPNet	ResNet101	61.85 ± 0.07	55.46 ± 0.08	44.41 ± 0.08	38.12 ± 0.37
46.85 ± 0.18	27.19 ± 0.14	3.05 ± 0.03	0.00 ± 0.00
45.85 ± 0.12	25.11 ± 0.09	2.54 ± 0.03	0.00 ± 0.00
48.74 ± 0.30	60.43 ± 0.26	91.27 ± 0.03
UNet	ResNet101	57.29 ± 0.20	50.30 ± 0.26	38.45 ± 0.36	31.93 ± 0.38
36.03 ± 0.33	20.81 ± 0.28	2.36 ± 0.08	0.00 ± 0.00
35.34 ± 0.32	19.23 ± 0.27	2.12 ± 0.05	0.00 ± 0.00
33.30 ± 0.36	42.07 ± 0.46	87.63 ± 0.22