Depth Estimation on KITTI Eigen split improved ground truth (test) benchmark leaderboard · SOTA2 Research

Depth Estimation on KITTI Eigen split improved ground truth (test)

0.067Abs RelDS-Depth

Evaluation Results

Method	Links
DS-Depth2023.08		0.067	0.359	3.314	0.109	94.6	98.9	99.7
ManyDepth2023.08		0.07	0.399	3.455	0.113	94.1	98.9	99.7
DORN2023.08		0.072	0.307	2.727	0.12	93.2	98.4	99.5
Packnet-SFM2023.08		0.078	0.42	3.485	0.121	93.1	98.6	99.6
Johnston et al.2023.08		0.081	0.484	3.716	0.126	92.7	98.5	99.6
Wang et al.2023.08		0.082	0.462	3.739	0.127	92.3	98.4	99.6
Monodepth22023.08		0.085	0.537	3.868	0.139	91.2	97.9	99.3
Patil et al.2023.08		0.087	0.495	3.775	0.133	91.7	98.3	99.5
Kuznietsov et al.2023.08		0.089	0.478	3.61	0.138	90.6	98	99.5
SuperDepth2023.08		0.09	0.542	3.967	0.144	90.1	97.6	99.3
Monodepth22023.08		0.09	0.545	3.942	0.137	91.4	98.3	99.5
3net (ResNet 50)2023.08		0.102	0.675	4.293	0.159	88.1	96.9	99.1
Monodepth2023.08		0.109	0.811	4.568	0.166	87.7	96.7	98.8
3net (VGG)2023.08		0.119	0.92	4.824	0.182	85.6	95.7	98.5
EPC++2023.08		0.12	0.789	4.755	0.177	85.6	96.1	98.7
EPC++2023.08		0.123	0.754	4.453	0.172	86.3	96.4	98.9
Ranjan2023.08		0.123	0.881	4.834	0.181	86	95.9	98.5
DDVO2023.08		0.126	0.866	4.932	0.185	85.1	95.8	98.6
Zhan FullNYU2023.08		0.13	1.52	5.184	0.205	85.9	95.5	98.1
GeoNet2023.08		0.132	0.994	5.24	0.193	83.3	95.3	98.5
Vid2Depth2023.08		0.134	0.983	5.501	0.203	82.7	94.4	98.1
SfMLearner2023.08		0.176	1.532	6.129	0.244	75.8	92.1	97.1