\begin{tabular}{c | c | c | c | c | c | c | c}
{\bf Method} & {\bf Setting} & {\bf IoU class} & {\bf iIoU class} & {\bf IoU category} & {\bf iIoU category} & {\bf Runtime} & {\bf Environment}\\ \hline
VideoProp-LabelRelax & & 72.82 \% & 48.68 \% & 88.99 \% & 75.26 \% & n s / GPU & B. Yi Zhu*: Improving Semantic Segmentation via Video Propagation and Label Relaxation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019.\\
DH-MDS & & 71.40 \% & 39.66 \% & 87.00 \% & 63.07 \% & 1.3 s / 1 core & \\
MapillaryAI\_ROB & & 69.56 \% & 43.17 \% & 86.52 \% & 68.89 \% & n s / 1 core & \\
Mapillary\_ROB & & 66.65 \% & 41.64 \% & 86.06 \% & 68.13 \% & n s / 1 core & \\
LDN2\_ROB & & 63.51 \% & 28.31 \% & 85.34 \% & 59.07 \% & 1 s / GPU & \\
AHiSS\_ROB & & 61.24 \% & 26.94 \% & 81.54 \% & 53.42 \% & 0.06 s / GPU & \\
IfN-DomAdap-Seg & & 59.50 \% & 30.28 \% & 81.57 \% & 61.91 \% & 1 s / GPU & J. Bolte, M. Kamp, A. Breuer, S. Homoceanu, P. Schlicht, F. Hüger, D. Lipinski and T. Fingscheidt: Unsupervised Domain Adaptation to Improve Image Segmentation Quality Both in the Source and Target Domain. Proc. of CVPR - Workshops 2019.\\
SegStereo & & 59.10 \% & 28.00 \% & 81.31 \% & 60.26 \% & 0.6 s / & G. Yang, H. Zhao, J. Shi, Z. Deng and J. Jia: SegStereo: Exploiting Semantic Information for Disparity Estimation. ECCV 2018.\\
RTS^2 Net & & 57.67 \% & 27.42 \% & 82.85 \% & 60.72 \% & 0.02 s / GPU & \\
SJTU\_HHW & & 56.52 \% & 23.83 \% & 78.98 \% & 50.85 \% & 1 s / GPU & \\
AdapNetv2\_ROB & & 54.97 \% & 25.20 \% & 81.64 \% & 56.31 \% & 1 s / 1 core & \\
VlocNet++\_ROB & & 53.92 \% & 23.68 \% & 80.74 \% & 53.66 \% & n s / 1 core & \\
HiSS\_ROB & & 53.16 \% & 21.37 \% & 78.32 \% & 51.92 \% & 0.06 s / GPU & \\
SDNet & & 51.14 \% & 17.74 \% & 79.62 \% & 50.45 \% & 0.2 s / GPU & M. Ochs, A. Kretz and R. Mester: SDNet: Semantic Guided Depth Estimation Network. German Conference on Pattern Recognition (GCPR) 2019.\\
APMoE\_seg\_ROB & & 47.96 \% & 17.86 \% & 78.11 \% & 49.17 \% & 0.2 s / GPU & S. Kong and C. Fowlkes: Pixel-wise Attentional Gating for Parsimonious Pixel Labeling. arxiv 1805.01556 2018.\\
BatMAN\_ROB & & 47.36 \% & 16.79 \% & 78.43 \% & 50.03 \% & 0.2 s / GPU & \\
FCN101\_ROB & & 24.57 \% & 6.19 \% & 51.85 \% & 22.81 \% & 0.07 s / 2 cores &
\end{tabular}