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Monocular Depth Estimation on Cityscapes (test)

5.14RMSEFree Sinewich
5.0045.9226.847.758Jul 12, 2024Nov 8, 2024Mar 8, 2025Jul 6, 2025Nov 3, 2025Mar 3, 2026Jul 1, 2026

Evaluation results

MethodLinks
Free SinewichBackbone=Swin-Tiny [26], Pre-trained=ImageNet-22K [7], Decoder=HRNet2026.035.14——————5.455.92
Flex-X-Large (Ours)Year=2026, T.F.=1, Data=M, FLOPs.(G)=19.62026.075.2680.0860.8770.13792.698.299.3——
Flex-Large (Ours)Year=2026, T.F.=1, Data=M, FLOPs.(G)=9.22026.075.310.0870.9110.13992.498.199.3——
Flex-Medium (Ours)Year=2026, T.F.=1, Data=M, FLOPs.(G)=8.02026.075.3580.0890.8850.14391.797.999.3——
TADFormerBackbone=Swin-Tiny [26], Pre-trained=ImageNet-22K [7], Decoder=HRNet2026.035.39——————3.445.97
DSI-MonoViTYear=2025, T.F.=1, Data=M, FLOPs.(G)=47.72026.075.410.0880.8720.14191.898.199.3——
ProDepthTest frames=2 (-1, 0), Semantics=false, W x H=416 x 1282024.075.5310.0950.8760.14690.897.899.3——
ProDepthYear=2024, T.F.=2(-1,0), Data=M, FLOPs.(G)=35.52026.075.5310.0950.8760.14690.897.899.3——
MTL - FullProtocol=MTL-Full, Backbone=Swin-Tiny [26], Pre-trained=ImageNet-22K [7], Decoder=HRNet2026.035.76——————-1.0328.49
FGTOYear=2024, T.F.=1, Data=M+Se, FLOPs.(G)=47.72026.075.8060.0960.930.15290.597.699.2——
Flex-Small (Ours)Year=2026, T.F.=1, Data=M, FLOPs.(G)=2.22026.075.8130.11.0780.15390.497.599.1——
MTLoRABackbone=Swin-Tiny [26], Pre-trained=ImageNet-22K [7], Decoder=HRNet2026.035.84——————-1.837.23
DynamicDepthTest frames=2 (-1, 0), Semantics=true, W x H=416 x 1282024.075.8670.10310.15789.597.499.1——
DynamicDepthYear=2022, T.F.=2(-1,0), Data=M+Se, FLOPs.(G)=18.5+2026.075.8670.10310.15789.597.499.1——
PuriLightYear=2026, T.F.=1, Data=M, FLOPs.(G)=5.72026.075.8920.0991.0140.15390.197.699.2——
Single TaskProtocol=Single Task, Backbone=Swin-Tiny [26], Pre-trained=ImageNet-22K [7], Decoder=HRNet2026.035.91——————056
Self-DistillationYear=2025, T.F.=1, Data=M, FLOPs.(G)=47.7+2026.076.0760.1181.0910.17385.49698.8——
Flex-Nano (Ours)Year=2026, T.F.=1, Data=M, FLOPs.(G)=0.62026.076.1330.1071.2610.16489.397.198.9——
ManyDepthTest frames=2 (-1, 0), Semantics=false, W x H=416 x 1282024.076.2230.1141.1930.1787.596.798.9——
ManyDepthYear=2021, T.F.=2(-1,0), Data=M, FLOPs.(G)=12.12026.076.2230.1141.1930.1787.596.798.9——
DiTASKBackbone=Swin-Tiny [26], Pre-trained=ImageNet-22K [7], Decoder=HRNet2026.036.35——————-9.892.58
InstaDMTest frames=1, Semantics=false, W x H=832 x 2562024.076.4370.1111.1580.18286.896.198.3——
MonoVitYear=2022, T.F.=1, Data=M, FLOPs.(G)=47.72026.076.5890.1141.2380.1748696.599——
Lee et al.Test frames=1, Semantics=false, W x H=832 x 2562024.076.6950.1161.2130.18685.295.198.2——
Monodepth2Test frames=1, Semantics=false, W x H=416 x 1282024.076.8760.1291.5690.18784.995.798.3——
Videos in the wildTest frames=1, Semantics=false, W x H=416 x 1282024.076.960.1271.330.1958394.798.1——
Li et al.Test frames=1, Semantics=false, W x H=416 x 1282024.076.980.1191.290.1984.695.298.2——
Struct2Depth 2Test frames=3 (-1, 0, +1), Semantics=true, W x H=416 x 1282024.077.0240.1512.4920.20282.693.797.2——
Struct2Depth 2Test frames=1, Semantics=false, W x H=416 x 1282024.077.280.1451.7370.20581.394.297.6——
Pilzer et al.Test frames=1, Semantics=false, W x H=512 x 2562024.078.0490.244.2640.3347187.193.7——
MTL - DecProtocol=MTL-Dec, Backbone=Swin-Tiny [26], Pre-trained=ImageNet-22K [7], Decoder=HRNet2026.038.54——————-30.590.97