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Monocular Depth Estimation on Cityscapes

93.1Accuracy (delta < 1.25)

SPIdepth

Updated 3d ago

Evaluation Results

Method
SPIdepth 2024.04	93.1	98.6	99.5	0.083	0.741	5.205	0.13	-	-
Ours-MonoViT 2023.12	92	98.1	99.4	0.088	0.795	5.368	0.14	-	-
RM-Depth 2023.03	91.3	98	99.3	0.09	0.825	5.503	0.143	-	-
RM-Depth 2024.04	91.3	98	99.3	0.09	0.825	5.503	0.143	-	-
ProDepth 2024.04	90.8	97.8	99.3	0.095	0.876	5.531	0.146	-	-
Ours-CADepth 2023.12	90.7	97.8	99.2	0.097	0.966	5.646	0.15	-	-
Ours-MonoViT 2023.12	90.5	97.6	99.2	0.096	0.93	5.806	0.152	-	-
Ours-Monodepth2 2023.12	89.6	97.3	99	0.102	1.024	6.015	0.159	-	-
Ours-HR-Depth 2023.12	89.6	97.4	99.1	0.1	1.01	5.998	0.157	-	-
DynamicDepth 2023.12	89.5	97.4	99.1	0.103	1	5.867	0.157	-	-
RM-Depth 2023.12	89.5	97.6	99.3	0.1	0.839	5.774	0.154	-	-
SQLdepth 2024.04	88.8	97.2	99	0.106	1.173	6.237	0.163	-	-
Ours-Monodepth2 2023.12	88.1	96.8	98.9	0.11	1.179	6.39	0.169	-	-
MonoViT 2023.12	88.1	97.4	99.1	0.106	1.098	6.071	0.16	-	-
ManyDepth 2021.04	87.5	96.7	98.9	0.114	1.193	6.223	0.17	-	-
ManyDepth 2024.04	87.5	96.7	98.9	0.114	1.193	6.223	0.17	-	-
Lee et al. 2023.03	86.8	96.1	98.3	0.111	1.158	6.437	0.182	-	-
InstaDM 2023.12	86.8	96.1	98.3	0.111	1.158	6.437	0.182	-	-
InstaDM 2024.04	86.8	96.1	98.3	0.111	1.158	6.437	0.182	-	-
Monodepth2 2023.12	86.5	96.4	98.8	0.125	1.474	6.688	0.18	-	-
CADepth 2023.12	86.2	96.2	98.6	0.124	1.278	6.771	0.183	-	-
MonoViT 2023.12	86	96.5	99	0.114	1.238	6.589	0.174	-	-
HR-Depth 2023.12	85.7	96.3	98.8	0.12	1.253	6.714	0.179	-	-
Lee et al. 2023.12	85.2	95.1	98.2	0.116	1.214	6.695	0.186	-	-
Lee et al. 2024.04	85.2	95.1	98.2	0.116	1.213	6.695	0.186	-	-
Monodepth2 2021.04	84.9	95.7	98.3	0.129	1.569	6.876	0.187	-	-
Monodepth2 2023.12	84.9	95.7	98.3	0.129	1.569	6.876	0.187	-	-
Monodepth2 2024.04	84.9	95.7	98.3	0.129	1.569	6.876	0.187	-	-
Li et al. 2021.04	84.6	95.2	98.2	0.119	1.29	6.98	0.19	-	-
Li et al. [28] 2023.03	84.6	95.2	98.2	0.119	1.29	6.98	0.19	-	-
Li et al. 2023.12	84.6	95.2	98.2	0.119	1.29	6.98	0.19	-	-
Li et al. 2024.04	84.6	95.2	98.2	0.119	1.29	6.98	0.19	-	-
GLNet 2023.03	84.3	93.8	97.6	0.129	1.044	5.361	0.212	-	-
Videos in the Wild 2021.04	83	94.7	98.1	0.127	1.33	6.96	0.195	-	-
Gordon et al. 2023.03	83	94.7	98.1	0.127	1.33	6.96	0.195	-	-
Gordon et al. 2023.12	83	94.7	98.1	0.127	1.33	6.96	0.195	-	-
Videos in the Wild 2024.04	83	94.7	98.1	0.127	1.33	6.96	0.195	-	-
ManyDepth 2021.04	82.7	95.4	98.5	0.137	1.578	7.249	0.197	-	-
Struct2Depth 2021.04	82.6	93.7	97.2	0.151	2.492	7.024	0.202	-	-
Struct2Depth 2021.04	81.3	94.2	97.6	0.145	1.737	7.28	0.205	-	-
Struct2Depth 2023.03	81.3	94.2	97.6	0.145	1.737	7.28	0.205	-	-
Struct2Depth 2023.12	81.3	94.2	97.6	0.145	1.737	7.28	0.205	-	-
Struct2Depth 2 2024.04	81.3	94.2	97.6	0.145	1.737	7.28	0.205	-	-
Monodepth2 2021.04	78.7	94.1	97.8	0.159	2.016	8.074	0.221	-	-
Struct2Depth 2021.04	77.4	90.8	95.4	0.222	5.737	8.613	0.258	-	-
AdaShare 2021.10	71.4	86.8	93.1	0.018	-	-	-	15.5	10.9
Pilzer et al. 2021.04	71	87.1	93.7	0.24	4.264	8.049	0.334	-	-
MTAN 2021.10	71	86.3	92.8	0.017	-	-	-	16.4	11.3
Pilzer et al. 2024.04	71	87.1	93.7	0.24	4.264	8.049	0.334	-	-
Cross-Stitch 2021.10	70	86.3	93.1	0.017	-	-	-	17.2	11.4
AutoMTL 2021.10	70	86.6	93.4	0.018	-	-	-	17.1	13.2
NDDR-CNN 2021.10	69.9	86.3	93	0.018	-	-	-	15.9	11.5
Sluice 2021.10	68.9	85.8	92.8	0.018	-	-	-	15.3	10.1
DEN 2021.10	68.2	84.5	91.6	0.018	-	-	-	11.3	6.8
Multi-Task 2021.10	58.8	80.5	89.9	0.026	-	-	-	1.5	3.1
Single-Task 2021.10	57.5	76.9	87	0.026	-	-	-	-	-
MP@Res5 2018.05	34.6	66.2	77.2	-	-	-	-	-	-
MultiPool 2018.05	34.5	65.7	76.9	-	-	-	-	-	-
MP@Res5 2018.05	33.7	65.9	76.9	-	-	-	-	-	-
MultiPool 2018.05	32	63.5	75.8	-	-	-	-	-	-
baseline 2018.05	29	53.8	75.8	-	-	-	-	-	-
MultiPool 2018.05	28.7	58.7	71.6	-	-	-	-	-	-