Table 14: Results: Cityscapes. 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	76.21 ± 0.05	70.32 ± 0.06	59.17 ± 0.38	51.62 ± 0.71
70.18 ± 0.16	52.64 ± 0.19	17.13 ± 0.13	5.00 ± 0.00
69.77 ± 0.16	51.40 ± 0.19	16.11 ± 0.07	5.00 ± 0.00
80.91 ± 0.17	88.33 ± 0.10	96.38 ± 0.01
DeepLabV3+	ResNet50	75.33 ± 0.12	69.31 ± 0.19	57.90 ± 0.31	51.30 ± 0.91
69.10 ± 0.30	51.65 ± 0.42	16.69 ± 0.40	4.67 ± 0.47
68.72 ± 0.22	50.39 ± 0.28	15.58 ± 0.25	4.67 ± 0.47
79.34 ± 0.36	86.85 ± 0.42	96.10 ± 0.06
DeepLabV3+	ResNet34	75.24 ± 0.07	69.19 ± 0.12	57.50 ± 0.55	50.39 ± 2.30
68.58 ± 0.17	50.96 ± 0.20	17.33 ± 0.48	5.00 ± 0.00
68.06 ± 0.20	49.45 ± 0.24	15.74 ± 0.46	5.00 ± 0.00
78.61 ± 0.14	86.54 ± 0.12	96.18 ± 0.04
DeepLabV3+	ResNet18	74.23 ± 0.04	68.07 ± 0.06	56.12 ± 0.36	49.65 ± 0.73
67.44 ± 0.11	49.80 ± 0.22	16.37 ± 0.28	4.67 ± 0.47
66.91 ± 0.18	48.35 ± 0.25	15.32 ± 0.17	5.00 ± 0.00
77.07 ± 0.17	85.31 ± 0.38	95.96 ± 0.03
DeepLabV3+	EfficientNetB0	74.60 ± 0.04	68.53 ± 0.10	57.38 ± 0.36	50.59 ± 1.21
67.60 ± 0.04	50.07 ± 0.10	17.43 ± 0.15	5.67 ± 0.47
66.98 ± 0.03	48.45 ± 0.06	16.04 ± 0.21	5.67 ± 0.47
77.40 ± 0.13	85.65 ± 0.12	96.07 ± 0.04
DeepLabV3+	MobileNetV2	73.60 ± 0.09	67.41 ± 0.07	55.49 ± 0.47	49.18 ± 0.87
66.79 ± 0.09	49.09 ± 0.09	15.43 ± 0.31	5.00 ± 0.00
66.38 ± 0.10	47.75 ± 0.08	14.58 ± 0.21	5.00 ± 0.00
75.40 ± 0.43	84.28 ± 0.44	95.78 ± 0.03
DeepLabV3+	MobileViTV2	75.06 ± 0.06	69.12 ± 0.12	58.02 ± 0.38	51.53 ± 0.96
68.47 ± 0.25	51.18 ± 0.25	17.80 ± 0.15	6.00 ± 0.00
67.99 ± 0.27	49.80 ± 0.28	16.47 ± 0.14	6.33 ± 0.47
78.17 ± 0.39	86.56 ± 0.19	96.10 ± 0.02
UPerNet	ResNet101	75.73 ± 0.04	69.66 ± 0.07	58.09 ± 0.22	51.61 ± 0.95
69.24 ± 0.17	51.66 ± 0.19	17.45 ± 0.08	4.67 ± 0.47
68.78 ± 0.10	50.36 ± 0.12	16.47 ± 0.09	5.00 ± 0.82
79.89 ± 0.10	87.22 ± 0.09	96.22 ± 0.04
UPerNet	ConvNeXt	77.13 ± 0.13	71.28 ± 0.19	60.41 ± 0.40	53.86 ± 0.81
71.22 ± 0.22	53.87 ± 0.33	19.48 ± 0.44	6.00 ± 0.00
70.75 ± 0.17	52.56 ± 0.27	17.98 ± 0.39	5.67 ± 0.47
81.81 ± 0.11	88.30 ± 0.07	96.62 ± 0.02
UPerNet	MiTB4	76.52 ± 0.16	70.82 ± 0.23	60.50 ± 0.64	56.09 ± 1.67
70.64 ± 0.11	53.55 ± 0.20	19.79 ± 0.33	6.33 ± 0.47
70.02 ± 0.13	51.88 ± 0.22	17.96 ± 0.33	6.33 ± 0.47
80.99 ± 0.20	88.10 ± 0.23	96.51 ± 0.04
SegFormer	MiTB4	76.78 ± 0.07	71.05 ± 0.13	60.12 ± 0.43	55.15 ± 1.36
70.68 ± 0.16	53.56 ± 0.14	19.95 ± 0.13	6.33 ± 0.47
70.14 ± 0.19	52.10 ± 0.18	18.22 ± 0.14	6.33 ± 0.47
80.75 ± 0.19	87.96 ± 0.17	96.55 ± 0.01
SegFormer	MiTB2	75.66 ± 0.07	69.86 ± 0.09	58.79 ± 0.31	53.77 ± 0.55
69.21 ± 0.16	51.86 ± 0.15	18.75 ± 0.41	6.33 ± 0.47
68.63 ± 0.14	50.41 ± 0.12	17.41 ± 0.36	6.33 ± 0.47
79.96 ± 0.05	87.40 ± 0.00	96.36 ± 0.01
DeepLabV3	ResNet101	75.26 ± 0.03	69.35 ± 0.07	58.44 ± 0.23	51.10 ± 0.68
69.10 ± 0.07	51.60 ± 0.12	16.91 ± 0.09	4.67 ± 0.47
68.51 ± 0.12	50.06 ± 0.15	15.79 ± 0.05	4.67 ± 0.47
80.07 ± 0.06	87.77 ± 0.13	96.25 ± 0.02
PSPNet	ResNet101	75.18 ± 0.07	69.27 ± 0.11	58.83 ± 0.29	53.18 ± 1.10
69.05 ± 0.15	51.53 ± 0.21	16.94 ± 0.08	5.00 ± 0.00
68.58 ± 0.14	50.18 ± 0.18	15.84 ± 0.09	5.00 ± 0.00
80.08 ± 0.13	87.62 ± 0.06	96.18 ± 0.05
UNet	ResNet101	75.36 ± 0.06	69.43 ± 0.07	58.16 ± 0.20	52.19 ± 0.94
68.79 ± 0.10	51.28 ± 0.08	16.59 ± 0.16	5.00 ± 0.00
68.31 ± 0.20	49.96 ± 0.22	15.66 ± 0.17	5.00 ± 0.00
77.12 ± 0.18	85.30 ± 0.04	96.05 ± 0.00