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Depth Prediction on Make3D C1 (test)

0.062Log10 Error (log10)DORN
-0.03660.628951.29451.96005Sep 13, 2016Dec 27, 2016Apr 11, 2017Jul 25, 2017Nov 7, 2017Feb 20, 2018Jun 6, 2018

Evaluation results

MethodLinks
DORNBackbone=ResNet2018.060.0620.1573.97——
Resnet50 10KBackbone=ResNet-50, Architecture=Multi-scale, Training data size=~10K image pairs2017.040.0650.1844.38——
MS-CRF2018.060.0650.1844.38——
Laina et al. (Huber loss)Loss function=Huber2017.040.0720.1764.46——
Laina et al.2018.060.0720.1764.46——
Resnet50-Multi-scaleBackbone=ResNet-50, Architecture=Multi-scale2017.040.0760.2064.51——
ResNet50-CascadeBackbone=ResNet-50, Architecture=Cascade2017.040.0820.2134.67——
DORNBackbone=VGG2018.060.0820.2367.02——
Laina et al.Supervised=true, Loss=berHu2016.090.082—5.4611.6650.198
Laina et al. (l2 loss)Loss function=l22017.040.0890.2234.89——
Li et al.2017.040.0920.2787.19——
Li et al.citation=[36]2018.060.0920.2787.12——
Liu et al.citation=[40]2018.060.1090.2877.36——
Liu et al. [20]2017.040.1190.3148.6——
Karsch et al.2017.040.1270.3559.2——
DepthTransfer2018.060.1270.3559.2——
Liu et al. [21]2017.040.1370.3359.49——
Liu et al.citation=[41]2018.060.1370.3359.49——
monodepthSupervised=false, Post-processing=true2016.090.142—8.867.1120.443
Karsch et al.Supervised=true2016.090.144—8.1724.8940.417
LRC2018.060.1560.44311.513——
monodepthSupervised=false2016.090.156—11.51311.990.535
Liu et al.Supervised=true2016.090.161—9.9726.6250.462
Kuznietsov et al.2018.060.190.4218.24——
Train set meanSupervised=true2016.090.223—11.54215.5170.893
LRC-Deep3D2018.062.527119.11——
monodepthIntegration=Deep3D [53], Supervised=false2016.092.527—19.1117.181