Monocular Depth Estimation on KITTI Improved Ground Truth 40 benchmark leaderboard · SOTA2 Research

Monocular Depth Estimation on KITTI Improved Ground Truth 40

0.068Abs Rel ErrorDynamicDepth

Evaluation Results

Method	Links
DynamicDepth2022.03		0.068	0.362	3.454	0.111	94.3	99.1	99.8
ManyDepth2022.03		0.07	0.399	3.455	0.113	94.1	98.9	99.7
DORN2022.03		0.072	0.307	2.727	0.12	93.2	98.4	99.5
Packnet-SFM2022.03		0.078	0.42	3.485	0.121	93.1	98.6	99.6
Johnston et al.2022.03		0.081	0.484	3.716	0.126	92.7	98.5	99.6
Wang et al.2022.03		0.082	0.462	3.739	0.127	92.3	98.4	99.6
Monodepth22022.03		0.085	0.537	3.868	0.139	91.2	97.9	99.3
Patil et al.2022.03		0.087	0.495	3.775	0.133	91.7	98.3	99.5
Kuznietsov et al.2022.03		0.089	0.478	3.61	0.138	90.6	98	99.5
SuperDepth2022.03		0.09	0.542	3.967	0.144	90.1	97.6	99.3
Monodepth22022.03		0.09	0.545	3.942	0.137	91.4	98.3	99.5
3net2022.03		0.102	0.675	4.293	0.159	88.1	96.9	99.1
Monodepth2022.03		0.109	0.841	4.568	0.166	87.7	96.7	98.8
3net2022.03		0.119	0.92	4.824	0.182	85.6	95.7	98.5
EPC++2022.03		0.12	0.789	4.755	0.177	85.6	96.1	98.7
EPC++2022.03		0.123	0.754	4.453	0.172	86.3	96.4	98.9
Ranjan2022.03		0.123	0.881	4.834	0.181	86	95.9	98.5
DDVO2022.03		0.126	0.866	4.932	0.185	85.1	95.8	98.6
Zhan FullNYU2022.03		0.13	1.52	5.184	0.205	82.9	95.5	98.1
GeoNet2022.03		0.132	0.994	5.24	0.193	83.3	95.3	98.5
Vid2Depth2022.03		0.134	0.983	5.501	0.203	82.7	94.4	98.1
SfMLearner2022.03		0.176	1.532	6.129	0.244	75.8	92.1	97.1