Table 1.

The number of trainable parameters (Pars) in millions (M), global accuracy (GA), and class accuracy (CA) for the CamVid test set

Method	Pars (M)	GA	CA
MS-D-Net (100 layers)	0.048	85.1	56.8
MS-D-Net (200 layers)	0.187	87.0	63.9
U-Net (3 scaling operations) (5)	1.863	83.2	50.4
U-Net (4 scaling operations) (5)	1.926	85.5	48.4
SegNet-Basic-EncoderAddition (4)	1.425	84.2	56.5
SegNet-Basic (4)	1.425	84.0	54.6
Boosting + Detectors + CRF (31)		83.8	62.5
Super Parsing (32)		83.3	51.2

The highest global accuracy, highest local accuracy, and smallest number of parameters out of all tested methods are shown in bold.