List your company

Monocular Depth Estimation on KITTI Improved GT (Eigen)

0.059AbsRelSCIPaD
0.055440.079470.10350.12753Sep 13, 2016May 2, 2018Dec 19, 2019Aug 7, 2021Mar 26, 2023Nov 11, 2024Jul 1, 2026

Evaluation results

MethodLinks
SCIPaDtraining=M, Resolution=192 x 6402024.070.0590.2872.8710.09596.4———99.399.8—
Jasminevariant=main2025.030.0610.2552.7650.09296.399.50.999————
SQLdepthtraining=M, Resolution=192 x 6402024.070.0610.3173.0550.195.7———99.299.7—
Flex-X-LargeType=Self-supervised, Params=32M, GFLOPs=25, Resolution=640×1922026.070.063——————95.2———
Jasmine*variant=*2025.030.0640.2942.9820.09795.799.40.998————
MonoViT2025.030.0680.3143.1250.10594.899.20.998————
DynamicDepthtraining=M, Resolution=192 x 6402024.070.0680.3623.4540.11194.3———99.199.8—
TriDepthtraining=M, Resolution=192 x 6402024.070.0680.3593.3410.1194.4———98.999.7—
SA4Depth + Hybrid-depthScaling=Median-scaled (done w/ GT), Training=M, Resolution=640 x 1922026.050.0680.3173.1030.105———95.299.299.82.71
ManyDepthtraining=M, Resolution=192 x 6402024.070.070.3993.4550.11394.1———98.999.7—
DA2 (ViT-L)Type=Zero-Shot, Params=335M, GFLOPs=1947, Resolution=1722×5182026.070.07——————95.6———
MonoViFi2025.030.0710.3383.5390.11393.7990.998————
SA4Depth + MonoViTScaling=Median-scaled (done w/ GT), Training=M, Resolution=640 x 1922026.050.0710.383.3410.111———94.598.999.70.16
Mono-ViFIScaling=Median-scaled (done w/ GT), Training=M+VI, Resolution=640 x 192, Post-processing=w/o2026.050.0720.3423.2540.111———94.199.199.83.32
Hybrid-depthScaling=Median-scaled (done w/ GT), Training=M, Resolution=640 x 1922026.050.0720.3343.2640.11———94.499.199.83.56
Depth Hints Resnet50Post-Processing=true, Data=SSGM, Resolution=320 x 10242021.060.0740.3633.1980.114———93.698.999.7—
Wavelet Monodepth Resnet50Post-Processing=true, Data=SSGM, Resolution=320 x 10242021.060.0740.3573.170.114———93.698.999.7—
DualRefineScaling=Median-scaled (done w/ GT), Training=M, Resolution=640 x 192, Post-processing=w/o2026.050.0750.3793.490.117———93.698.999.73.39
MonoViTScaling=Median-scaled (done w/ GT), Training=M, Resolution=640 x 1922026.050.0750.3893.4190.115———93.898.999.73.73
Wavelet Monodepth Resnet50Post-Processing=true, Data=S, Resolution=320 x 10242021.060.0760.4133.4340.126———92.698.499.5—
Depth HintsPost-Processing=true, Data=SSGM, Resolution=320 x 10242021.060.0770.4043.3450.119———9398.899.7—
SA4Depth + MonoViTScaling=scale-aware (Learned metric), Training=M+v, Resolution=640 x 1922026.050.0770.4043.4720.119———93.298.899.70.05
DA2 (ViT-S)Type=Zero-Shot, Params=25M, GFLOPs=137, Resolution=1722×5182026.070.077——————94.4———
PackNet-SfMtraining=M, Resolution=192 x 6402024.070.0780.423.4850.12193.1———98.699.6—
Wavelet Monodepth Resnet18Post-Processing=true, Data=SSGM, Resolution=320 x 10242021.060.0780.3973.3160.121———92.898.799.7—
PackNet-SfMScaling=Median-scaled (done w/ GT), Training=M, Resolution=640 x 192, Post-processing=w/o2026.050.0780.423.4850.121———93.198.699.60.75
Monodepth2 Resnet18Post-Processing=true, Data=S, Resolution=192 x 6402021.060.0790.5123.7210.131———92.498.299.4—
Monodepth2training=MS, Resolution=192 x 6402024.070.080.4663.6810.12792.6———98.599.5—
Wavelet Monodepth Resnet18Post-Processing=true, Data=S, Resolution=320 x 10242021.060.080.4433.5440.13———91.998.399.5—
SA4Depth + Monodepth2-50Scaling=Median-scaled (done w/ GT), Training=M, Backbone=ResNet-50, Resolution=640 x 1922026.050.080.4653.7070.125———92.898.699.61.9
Lotus2025.030.081———93.198.7—————
Wavelet Monodepth Resnet50Post-Processing=true, Data=S, Resolution=192 x 6402021.060.0810.4773.6580.133———9298.199.4—
Depth Hints Resnet50Post-Processing=true, Data=SSGM, Resolution=192 x 6402021.060.0810.4323.510.124———92.498.599.6—
Wavelet Monodepth Resnet50Post-Processing=true, Data=SSGM, Resolution=192 x 6402021.060.0810.4493.5090.125———92.398.699.6—
Monodepth2 Resnet18Post-Processing=true, Data=S, Resolution=320 x 10242021.060.0820.4973.6370.132———92.498.299.4—
Wavelet Monodepth Resnet18Post-Processing=true, Data=SSGM, Resolution=192 x 6402021.060.0830.4763.6350.129———9298.399.5—
Wavelet Monodepth Resnet18Post-Processing=true, Data=S, Resolution=192 x 6402021.060.0840.5233.8070.137———91.49899.4—
Monodepth2 Resnet18Post-Processing=true, Data=MS, Resolution=192 x 6402021.060.0840.4943.7390.132———91.898.399.5—
Depth HintsPost-Processing=true, Data=SSGM, Resolution=192 x 6402021.060.0850.4873.670.131———91.798.399.6—
Wavelet Monodepth Resnet18Post-Processing=true, Data=MS, Resolution=192 x 6402021.060.0850.4973.8040.134———91.298.299.5—
Monodepth2-50Scaling=Median-scaled (done w/ GT), Training=M, Backbone=ResNet-50, Resolution=640 x 1922026.050.0850.4683.6740.128———92.198.599.62.65
SA4Depth + Monodepth2-50Scaling=scale-aware (Learned metric), Training=M+v, Backbone=ResNet-50, Resolution=640 x 1922026.050.0850.4763.7820.133———91.498.399.50.06
Wavelet Monodepth Resnet18Post-Processing=true, Data=MS + SSGM, Resolution=192 x 6402021.060.0860.4973.6990.131———91.498.399.6—
Depth HintsPost-Processing=true, Data=MS + SSGM, Resolution=192 x 6402021.060.0870.5263.7760.133———91.598.299.5—
SA4Depth + Monodepth2-18Scaling=Median-scaled (done w/ GT), Training=M, Backbone=ResNet-18, Resolution=640 x 1922026.050.0870.5243.910.134———91.898.299.50.09
SA4Depth + Monodepth2-18Scaling=scale-aware (Learned metric), Training=M+v, Backbone=ResNet-18, Resolution=640 x 1922026.050.0880.5563.9380.138———919899.40.06
MonoViTScaling=scale-aware (Learned metric), Training=M+v, Resolution=640 x 1922026.050.0890.4663.590.129———91.398.599.60.07
JasmineNotes=Mono, Data=KH(68K+0), Alignment=Alternative alignment discussed in Sec. 4.32025.030.090.5813.9440.16191.997.298.6————
Monodepth2-18Scaling=Median-scaled (done w/ GT), Training=M, Backbone=ResNet-18, Resolution=640 x 1922026.050.090.5453.9420.137———91.498.399.52.79
Jaeho et al*Venue=CVPR2024, Notes=Mono, Data=K(40K+0)2025.030.0910.6044.0660.16491.39798.6————
RPrDepthVenue=ECCV2024, Notes=Mono, Data=K(40K+0)2025.030.0910.6124.0980.1629197.198.6————
FUMETScaling=scale-aware (Learned metric), Training=M+SI, Resolution=640 x 1922026.050.0910.5333.8920.136———90.698.399.50.07
Monodepth2-18Scaling=scale-aware (Learned metric), Training=M+v, Backbone=ResNet-18, Resolution=640 x 1922026.050.0920.5493.9950.142———90.29899.40.07
DA2 (ViT-L)Type=Zero-Shot, Params=335M, GFLOPs=276, Resolution=644×1962026.070.092——————91.5———
Mono-ViFIVenue=ECCV2024, Notes=Mono, Data=K(40K+0)2025.030.0930.5894.0720.16890.996.998.5————
VADepthScaling=scale-aware (Learned metric), Training=M+camH, Resolution=640 x 1922026.050.0930.4933.7040.132———91.398.499.60.07
Monodepth2-50Scaling=scale-aware (Learned metric), Training=M+v, Backbone=ResNet-50, Resolution=640 x 1922026.050.0930.5593.9840.14———90.198.199.50.07
DaCCNVenue=ICCV2023, Notes=Mono, Data=K(40K+0)2025.030.0940.6244.1450.16990.99798.5————
E2E-FT2025.030.096———92.198—————
MonoViTVenue=3DV 2022, Notes=Mono, Data=K(40K+0)2025.030.0960.7144.2920.17290.896.898.4————
SD-SSMDEVenue=CVPR2022, Notes=Mono, Data=K(40K+0)2025.030.0980.6744.1870.1790.296.898.5————
Marigold2025.030.099———91.698.7—————
DepthSegNetVenue=ECCV2022, Notes=Mono, Data=K(40K+0)2025.030.0990.6244.1650.17190.296.998.5————
DevNetVenue=ECCV2022, Notes=Mono, Data=K(40K+0)2025.030.10.6994.4120.17489.396.698.5————
Jasmine*Notes=Mono, Data=KH(68K+0), Alignment=Standard alignment discussed in Sec. 4.32025.030.1020.543.7280.16290.797.398.7————
LiteMonoVenue=CVPR2023, Notes=Mono, Data=K(40K+0)2025.030.1020.7464.4440.17989.696.598.3————
HR-DepthVenue=AAAI2021, Notes=Mono, Data=K(40K+0)2025.030.1060.7554.4720.18189.296.698.4————
R-MSFM6Venue=ICCV2021, Notes=Mono, Data=K(40K+0)2025.030.1080.7484.470.18588.996.398.2————
monodepthSupervised=false, Training Dataset=CS + K, Backbone=ResNet, Post-processing=true, Evaluation cap=50m2016.090.1080.6573.7290.19487.395.497.9————
Wang et al.Supervision=M2023.040.1090.7794.6410.18688.396.298.2————
LotusVenue=ICLR2025, Notes=ZeroShot, Data=Syn(59K+59K)2025.030.110.6113.8070.17589.29798.6————
DA2 (ViT-S)Type=Zero-Shot, Params=25M, GFLOPs=19, Resolution=644×1962026.070.11——————88.1———
PackNet-SfMSupervision=M+v, Backbone=ResNet-182023.040.1110.8294.7880.19986.495.498————
E2E FTVenue=WACV2025, Notes=ZeroShot, Data=Syn(74K+74K)2025.030.1120.6494.0990.188996.998.5————
G2SSupervision=M+v, Backbone=ResNet-502023.040.1120.8944.8520.19287.795.898.1————
VA-DepthSupervision=M+h2023.040.1120.8644.8040.1987.895.998.2————
monodepthSupervised=false, Training Dataset=CS + K, Post-processing=true, Evaluation cap=50m2016.090.1120.683.810.19886.695.397.9————
DNetSupervision=M+h2023.040.1130.8644.8120.19187.79698.1————
pRGBD-RefinedSupervision=M+SLAM2023.040.1130.7934.6550.18887.49698.3————
Kuznietsov et al.Supervision=M+D2023.040.1130.7414.6210.18986.29698.6————
TrainFlowSupervision=M+SfM2023.040.1130.7044.5810.18487.196.198.4————
TC-DepthSupervision=M, config=only Lgeo2023.040.1130.9044.7730.19387.795.998————
OursSupervision=M2023.040.1130.8514.8090.19187.795.998.1————
monodepthSupervised=false, Training Dataset=CS + K, Backbone=ResNet, Post-processing=true2016.090.1140.8984.9350.20686.194.997.6————
Monodepth2Venue=ICCV2019, Notes=Mono, Data=K(40K+0)2025.030.1150.8824.7010.1987.996.198.2————
Monodepth2Supervision=M2023.040.1150.9034.8630.19387.795.998.1————
monodepthSupervised=false, Training Dataset=CS + K, Evaluation cap=50m2016.090.1170.7623.9720.2068694.897.6————
Sparse-to-ContSupervision=M+D2023.040.1180.634.520.20989.896.698.5————
monodepthSupervised=false, Training Dataset=CS + K, Post-processing=true2016.090.1180.9235.0150.2185.494.797.6————
SC-SfMLearnerSupervision=M2023.040.1190.8574.950.19786.395.798.1————
MarigoldVenue=CVPR2024, Notes=ZeroShot, Data=Syn(74K+74K)2025.030.120.6724.0330.18487.496.898.5————
monodepthSupervised=false, Training Dataset=CS + K2016.090.1241.0765.3110.21984.794.297.3————
Godard et al.Training Dataset=Cityscapes + KITTI, Pose Supervision=true2017.040.1241.0765.3110.219———84.794.297.3—
Li et al.Supervision=M2023.040.130.955.1380.20984.394.897.8————
monodepthSupervised=false, Training Dataset=CS + K, Backbone=ResNet, Post-processing=true, Crop Strategy=uncropped2016.090.131.1975.2220.22684.39497.1————
monodepthSupervised=false, Training Dataset=CS + K, Post-processing=true, Crop Strategy=uncropped2016.090.1341.2615.3360.2383.593.897.1————
Sheng et al.Supervision=M2023.040.1391.0215.4180.20980.393.797.6————
monodepthSupervised=false, Training Dataset=K, Evaluation cap=50m2016.090.140.9764.4710.23281.893.196.9————
monodepthSupervised=false, Training Dataset=K2016.090.1481.3445.9270.24780.392.296.4————
Godard et al.Training Dataset=KITTI, Pose Supervision=true2017.040.1481.3445.9270.247———80.392.296.4—