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Odometry Estimation on KITTI Odometry Sequence 09

0.012Absolute Trajectory ErrorGeoNet
0.010480.020740.0310.04126Jun 4, 2018

Evaluation results

MethodLinks
GeoNet# frames=5, Evaluation Protocol=Standard2018.060.012——
Ranjan# frames=5, Evaluation Protocol=Standard2018.060.012——
EPC++ MS# frames=3, Evaluation Protocol=Standard2018.060.012——
Mahjourian# frames=3, Evaluation Protocol=Standard2018.060.013——
EPC++ M# frames=3, Evaluation Protocol=Standard2018.060.013——
ORB-SlamEvaluation Protocol=Standard2018.060.014——
Zhou# frames=5, Evaluation Protocol=Online implementation (newer results)2018.060.016——
Monodepth2 M# frames=2, Evaluation Protocol=Pairwise predictions, Pre-training=Yes2018.060.017——
Monodepth2 MS# frames=2, Evaluation Protocol=Pairwise predictions, Pre-training=Yes2018.060.017——
Monodepth2 M# frames=2, Evaluation Protocol=Pairwise predictions, Pre-training=No2018.060.018——
Monodepth2 MS# frames=2, Evaluation Protocol=Pairwise predictions, Pre-training=No2018.060.018——
Zhou# frames=5, Evaluation Protocol=Standard2018.060.021——
DDVO# frames=3, Evaluation Protocol=Standard2018.060.045——
Zhou# frames=2, Evaluation Protocol=Pairwise predictions2018.060.05——
Bian2026.05—11.23.35
CCNet2021.04—0.06921.77
CoopNet2026.05—8.422.66
Deep Two-View SfMTraining=Synthetic data2021.04—0.0170.48
GANVO2021.04—0.11523.53
LTMVO2021.04—0.03491.03
ORB2026.05—15.30.26
SfMLearner2021.04—0.08283.07
Zhou2026.05—17.846.78