Depth Prediction on KITTI original ground truth (test) benchmark leaderboard · SOTA2 Research

Depth Prediction on KITTI original ground truth (test)

0.096Abs RelDynamicDepth

Evaluation Results

Method	Links
DynamicDepth2022.03		0.096	0.72	4.458	0.175	89.7	96.4	98.4
ManyDepth2022.03		0.098	0.77	4.459	0.176	90	96.5	98.3
Dorn2022.03		0.099	0.593	3.714	0.161	89.7	96.6	98.6
FeatDepth2022.03		0.099	0.697	4.427	0.184	88.9	96.3	98.2
DepthHint2022.03		0.1	0.728	4.469	0.185	88.5	96.2	98.2
Guizilini et al.2022.03		0.102	0.698	4.381	0.178	89.6	96.4	98.4
FeatDepth2022.03		0.104	0.729	4.481	0.179	89.3	96.5	98.4
Wang et al.2022.03		0.106	0.799	4.662	0.187	88.9	96.1	98.2
Johnston et al.2022.03		0.106	0.861	4.699	0.185	88.9	96.2	98.2
MonoDepth22022.03		0.107	0.849	4.764	0.201	87.4	95.3	97.7
Gur et al.2022.03		0.11	0.666	4.186	0.168	88	96.6	98.8
MonoResMatch2022.03		0.111	0.867	4.714	0.199	86.4	95.4	97.9
Patil et al.2022.03		0.111	0.821	4.65	0.187	88.3	96.1	98.2
Packnet-SFM2022.03		0.111	0.785	4.601	0.189	87.8	96	98.2
InstaDM2022.03		0.112	0.777	4.772	0.191	87.2	95.9	98.2
Kuznietsov et al.2022.03		0.113	0.741	4.621	0.189	86.2	96	98.6
Lee et al.2022.03		0.114	0.876	4.715	0.191	87.2	95.5	98.1
Monodepth22022.03		0.115	0.903	4.863	0.193	87.7	95.9	98.1
SuperDepth2022.03		0.116	1.055	—	0.209	85.3	94.8	97.7
DualNet2022.03		0.121	0.837	4.945	0.197	85.3	95.5	98.2
MonoDispNet2022.03		0.126	0.832	4.172	0.217	84	94.1	97.3
EPC++2022.03		0.128	0.935	5.011	0.209	83.1	94.5	97.9
Videos in the wild2022.03		0.128	0.959	5.23	0.212	84.5	94.7	97.6
Li et al.2022.03		0.13	0.95	5.138	0.209	84.3	94.8	97.8
MonoDepth2022.03		0.133	1.142	5.533	0.23	83	93.6	97
SIGNet2022.03		0.133	0.905	5.181	0.208	82.5	94.7	98.1
Zhan FullNYU2022.03		0.135	1.132	5.585	0.229	82	93.3	97.1
DFR2022.03		0.135	1.132	5.585	0.229	82	93.3	97.1
EPC++2022.03		0.141	1.029	5.35	0.216	81.6	94.1	97.6
Struct2depth (M)2022.03		0.141	1.026	5.291	0.215	81.6	94.5	97.9
Ranjan et al.2022.03		0.148	1.149	5.464	0.223	81.5	93.5	97.3
DF-Net2022.03		0.15	1.124	5.507	0.226	80.6	93.3	97.3
DDVO2022.03		0.151	1.257	5.583	0.228	81	93.6	97.4
GeoNet2022.03		0.155	1.296	5.857	0.233	79.3	93.1	97.3
LEGO2022.03		0.162	1.352	6.276	0.252	78.3	92.1	96.9
Vid2Depth2022.03		0.163	1.24	6.22	0.25	76.2	91.6	96.8
UnDeepVO2022.03		0.183	1.73	6.57	0.268	—	—	—
SfMLearner2022.03		0.208	1.768	6.958	0.283	67.8	88.5	95.7