Monocular Depth Estimation on KITTI (AbsRel, RMSE, Delta 1-3) benchmark leaderboard · SOTA2 Research

Monocular Depth Estimation on KITTI (AbsRel, RMSE, Delta 1-3)

4.3AbsRelDINOv3-L+LFR

Evaluation Results

Method	Links
DINOv3-L+LFR2026.04		4.3	0.099	6.3	1.711	98.8	99.9	100
DAR-L2026.04		4.4	0.11	6.7	1.799	98.6	99.9	100
DA v22026.04		4.5	—	6.7	1.861	98.3	99.8	100
DAR-B2026.04		4.6	0.114	6.9	1.832	98.5	99.9	100
DA v12026.04		4.6	—	6.9	1.896	98.2	99.8	100
DINOv3-L2026.04		4.6	0.107	6.7	1.794	98.6	99.9	100
EcoDepth2026.04		4.8	0.139	7.4	2.039	97.9	99.8	99.9
DINOv3-B+LFR2026.04		4.9	0.128	7.2	1.931	98.1	99.8	100
IEBins2026.04		5	0.142	7.5	2.011	97.8	99.8	99.9
MIM2026.04		5	0.139	7.5	1.966	97.7	99.8	100
DDP2026.04		5	0.148	7.6	2.072	97.5	99.7	99.9
PixelFormer2026.04		5.1	0.149	7.7	2.081	97.6	99.7	99.9
NeWCRFs2026.04		5.2	0.155	7.9	2.129	97.4	99.7	99.9
ZoeDepth2026.04		5.4	0.189	8.3	2.44	97	99.6	99.9
DINOv3-B2026.04		5.7	0.145	7.7	1.998	97.9	99.8	100
BTS2026.04		5.9	0.241	9.6	2.756	95.6	99.3	99.8
DPT2026.04		6	—	9.2	2.573	95.9	99.5	99.6
SS3D + VLRC2026.07		6	0.496	13.3	2.908	95	97.8	98.6
SS3D2026.07		6.4	0.53	13.8	3.212	94.6	97.7	98.6
AdaBins2026.04		6.7	0.19	8.8	2.96	94.9	99.2	99.8
P3Depth2026.04		7.1	0.27	10.3	2.842	95.3	99.3	99.8
DORN2026.04		7.2	0.307	12	2.727	93.2	98.4	99.4
Hariat et al.2026.07		8.2	0.604	16.2	4.108	92.8	96.8	98.5
RA-Depth2026.07		9.6	0.613	17.1	4.216	90.3	96.8	98.5
MonoViT2026.07		9.9	0.708	17.5	4.372	90	96.7	98.4
DIFFNet2026.07		10.2	0.764	18	4.483	89.6	96.5	98.3
HR-Depth2026.07		10.9	0.792	18.5	4.632	88.4	96.2	98.3
Monodepth22026.07		11	0.831	18.7	4.642	88.3	96.2	98.2
Ours2026.06		13.71	0.5361	15.58	3.4067	85.42	98.81	99.76
MoGeV22026.06		18.22	0.6595	21.91	3.8175	61.42	97.86	99.7
DepthPro2026.06		18.33	0.74	18.72	3.6684	73.61	98.13	99.72
Eigenetal2026.04		20.3	1.517	28.2	6.307	70.2	89.8	96.7
DA32026.06		22.63	1.0362	21.98	4.4589	55.12	98.6	99.64