3D on NYU-Depth V2

Metric: Delta < 1.25 (higher is better)

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#	Model↕	Delta < 1.25▼	Augmentations	Paper	Date↕	Code
1	UniK3D (FT, metric)	0.989	No	UniK3D: Universal Camera Monocular 3D Estimation	2025-03-20	Code
2	Metric3Dv2(L, FT)	0.989	Yes	Metric3Dv2: A Versatile Monocular Geometric Foun...	2024-03-22	Code
3	HybridDepth	0.988	No	HybridDepth: Robust Metric Depth Fusion by Lever...	2024-07-26	Code
4	UniDepthV2 (FT, metric)	0.988	Yes	UniDepthV2: Universal Monocular Metric Depth Est...	2025-02-27	Code
5	Depth Anything	0.984	Yes	Depth Anything: Unleashing the Power of Large-Sc...	2024-01-19	Code
6	UniDepth (Zero-shot)	0.984	Yes	UniDepth: Universal Monocular Metric Depth Estim...	2024-03-27	Code
7	Distill Any Depth	0.981	No	Distill Any Depth: Distillation Creates a Strong...	2025-02-26	Code
8	FutureDepth	0.981	No	FutureDepth: Learning to Predict the Future Impr...	2024-03-19	-
9	ECoDepth	0.978	No	ECoDepth: Effective Conditioning of Diffusion Mo...	2024-03-27	Code
10	PrimeDepth + Depth Anything	0.977	No	PrimeDepth: Efficient Monocular Depth Estimation...	2024-09-13	Code
11	MetaPrompt-SD	0.976	Yes	Harnessing Diffusion Models for Visual Perceptio...	2023-12-22	Code
12	EVP	0.976	No	EVP: Enhanced Visual Perception using Inverse Mu...	2023-12-13	Code
13	TADP	0.976	Yes	Text-image Alignment for Diffusion-based Percept...	2023-09-29	Code
14	DepthMaster	0.972	Yes	DepthMaster: Taming Diffusion Models for Monocul...	2025-01-05	Code
15	PolyMaX(ConvNeXt-L)	0.969	Yes	PolyMaX: General Dense Prediction with Mask Tran...	2023-11-09	Code
16	Marigold + E2E FT(zero-shot)	0.966	No	Fine-Tuning Image-Conditional Diffusion Models i...	2024-09-17	Code
17	PrimeDepth	0.966	No	PrimeDepth: Efficient Monocular Depth Estimation...	2024-09-13	Code
18	Marigold	0.964	Yes	Repurposing Diffusion-Based Image Generators for...	2023-12-04	Code
19	MeSa	0.964	No	MeSa: Masked, Geometric, and Supervised Pre-trai...	2023-10-06	-
20	VPD	0.964	No	Unleashing Text-to-Image Diffusion Models for Vi...	2023-03-03	Code
21	ScaleDepth-N	0.957	No	ScaleDepth: Decomposing Metric Depth Estimation ...	2024-07-11	Code
22	ZoeD-M12-N	0.955	Yes	ZoeDepth: Zero-shot Transfer by Combining Relati...	2023-02-23	Code
23	AiT-P(SwinV2-L)	0.954	No	All in Tokens: Unifying Output Space of Visual T...	2023-01-05	Code
24	DMD	0.953	Yes	Zero-Shot Metric Depth with a Field-of-View Cond...	2023-12-20	-
25	DINOv2 (ViT-g/14 frozen, w/ DPT decoder)	0.9497	Yes	DINOv2: Learning Robust Visual Features without ...	2023-04-14	Code
26	NVDS(DPT-L)	0.9493	Yes	NVDS+: Towards Efficient and Versatile Neural St...	2023-07-17	Code
27	SwinV2-L 1K-MIM	0.949	No	Revealing the Dark Secrets of Masked Image Model...	2022-05-26	Code
28	DepthGen	0.946	Yes	Monocular Depth Estimation using Diffusion Models	2023-02-28	-
29	Metric3D (ConvNeXt-Large, Zero-shot testing)	0.944	Yes	Metric3D: Towards Zero-shot Metric 3D Prediction...	2023-07-20	Code
30	VA-DepthNet(SwinV1-L)	0.937	No	VA-DepthNet: A Variational Approach to Single Im...	2023-02-13	Code
31	MIM-Swin-V2	0.9361	No	Analysis of NaN Divergence in Training Monocular...	2023-11-07	-
32	NDDepth	0.936	No	NDDepth: Normal-Distance Assisted Monocular Dept...	2023-09-19	Code
33	IEBins	0.936	No	IEBins: Iterative Elastic Bins for Monocular Dep...	2023-09-25	Code
34	URCDC-Depth	0.933	No	URCDC-Depth: Uncertainty Rectified Cross-Distill...	2023-02-16	Code
35	OrdinalEntropy	0.932	No	Improving Deep Regression with Ordinal Entropy	2023-01-21	Code
36	Gaming for Depth (GfD)	0.931	Yes	-	-	-
37	PixelFormer	0.929	No	Attention Attention Everywhere: Monocular Depth ...	2022-10-17	Code
38	BinsFormer	0.925	No	BinsFormer: Revisiting Adaptive Bins for Monocul...	2022-04-03	Code
39	NeWCRFs	0.922	No	NeW CRFs: Neural Window Fully-connected CRFs for...	2022-03-03	Code
40	DDP (step3)	0.921	No	DDP: Diffusion Model for Dense Visual Prediction	2023-03-30	Code
41	DepthFormer	0.921	No	DepthFormer: Exploiting Long-Range Correlation a...	2022-03-27	Code
42	D-Net	0.919	No	-	-	Code
43	LeReS	0.916	Yes	Learning to Recover 3D Scene Shape from a Single...	2020-12-17	Code
44	GLPDepth	0.915	No	Global-Local Path Networks for Monocular Depth E...	2022-01-19	Code
45	Depth-Map-Decomposition-HRWSI	0.913	Yes	Depth Map Decomposition for Monocular Depth Esti...	2022-08-23	Code
46	Depthformer	0.913	No	Depthformer : Multiscale Vision Transformer For ...	2022-07-10	Code
47	LocalBins	0.91	No	LocalBins: Improving Depth Estimation by Learnin...	2022-03-28	Code
48	IronDepth	0.91	No	IronDepth: Iterative Refinement of Single-View D...	2022-10-07	Code
49	Depth-Map-Decomposition	0.907	No	Depth Map Decomposition for Monocular Depth Esti...	2022-08-23	Code
50	DPT-Hybrid	0.904	Yes	Vision Transformers for Dense Prediction	2021-03-24	Code
51	AdaBins	0.903	No	AdaBins: Depth Estimation using Adaptive Bins	2020-11-28	Code
52	CutDepth	0.899	Yes	CutDepth:Edge-aware Data Augmentation in Depth E...	2021-07-16	Code
53	P3Depth	0.898	No	P3Depth: Monocular Depth Estimation with a Piece...	2022-04-05	Code
54	LapDepth	0.895	No	-	-	Code
55	VNL	0.875	No	Enforcing geometric constraints of virtual norma...	2019-07-29	Code
56	Focal-WNet	0.875	No	-	-	Code
57	SC-DepthV2	0.82	No	Auto-Rectify Network for Unsupervised Indoor Dep...	2020-06-04	Code

#1UniK3D (FT, metric)
0.989
Delta < 1.25· 2025-03-20
UniK3D: Universal Camera Monocular 3D Estimation Code
#2Metric3Dv2(L, FT)SOTA
0.989
Delta < 1.25· Augmentations· 2024-03-22
Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation Code
#3HybridDepth
0.988
Delta < 1.25· 2024-07-26
HybridDepth: Robust Metric Depth Fusion by Leveraging Depth from Focus and Single-Image Priors Code
#4UniDepthV2 (FT, metric)
0.988
Delta < 1.25· Augmentations· 2025-02-27
UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler Code
#5Depth AnythingSOTA
0.984
Delta < 1.25· Augmentations· 2024-01-19
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data Code
#6UniDepth (Zero-shot)
0.984
Delta < 1.25· Augmentations· 2024-03-27
UniDepth: Universal Monocular Metric Depth Estimation Code
#7Distill Any Depth
0.981
Delta < 1.25· 2025-02-26
Distill Any Depth: Distillation Creates a Stronger Monocular Depth Estimator Code
#8FutureDepth
0.981
Delta < 1.25· 2024-03-19
FutureDepth: Learning to Predict the Future Improves Video Depth Estimation
#9ECoDepth
0.978
Delta < 1.25· 2024-03-27
ECoDepth: Effective Conditioning of Diffusion Models for Monocular Depth Estimation Code
#10PrimeDepth + Depth Anything
0.977
Delta < 1.25· 2024-09-13
PrimeDepth: Efficient Monocular Depth Estimation with a Stable Diffusion Preimage Code
#11MetaPrompt-SD
0.976
Delta < 1.25· Augmentations· 2023-12-22
Harnessing Diffusion Models for Visual Perception with Meta Prompts Code
#12EVP
0.976
Delta < 1.25· 2023-12-13
EVP: Enhanced Visual Perception using Inverse Multi-Attentive Feature Refinement and Regularized Image-Text Alignment Code
#13TADPSOTA
0.976
Delta < 1.25· Augmentations· 2023-09-29
Text-image Alignment for Diffusion-based Perception Code
#14DepthMaster
0.972
Delta < 1.25· Augmentations· 2025-01-05
DepthMaster: Taming Diffusion Models for Monocular Depth Estimation Code
#15PolyMaX(ConvNeXt-L)
0.969
Delta < 1.25· Augmentations· 2023-11-09
PolyMaX: General Dense Prediction with Mask Transformer Code
#16Marigold + E2E FT(zero-shot)
0.966
Delta < 1.25· 2024-09-17
Fine-Tuning Image-Conditional Diffusion Models is Easier than You Think Code
#17PrimeDepth
0.966
Delta < 1.25· 2024-09-13
PrimeDepth: Efficient Monocular Depth Estimation with a Stable Diffusion Preimage Code
#18Marigold
0.964
Delta < 1.25· Augmentations· 2023-12-04
Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation Code
#19MeSa
0.964
Delta < 1.25· 2023-10-06
MeSa: Masked, Geometric, and Supervised Pre-training for Monocular Depth Estimation
#20VPDSOTA
0.964
Delta < 1.25· 2023-03-03
Unleashing Text-to-Image Diffusion Models for Visual Perception Code
#21ScaleDepth-N
0.957
Delta < 1.25· 2024-07-11
ScaleDepth: Decomposing Metric Depth Estimation into Scale Prediction and Relative Depth Estimation Code
#22ZoeD-M12-NSOTA
0.955
Delta < 1.25· Augmentations· 2023-02-23
ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth Code
#23AiT-P(SwinV2-L)SOTA
0.954
Delta < 1.25· 2023-01-05
All in Tokens: Unifying Output Space of Visual Tasks via Soft Token Code
#24DMD
0.953
Delta < 1.25· Augmentations· 2023-12-20
Zero-Shot Metric Depth with a Field-of-View Conditioned Diffusion Model
#25DINOv2 (ViT-g/14 frozen, w/ DPT decoder)
0.9497
Delta < 1.25· Augmentations· 2023-04-14
DINOv2: Learning Robust Visual Features without Supervision Code
#26NVDS(DPT-L)
0.9493
Delta < 1.25· Augmentations· 2023-07-17
NVDS+: Towards Efficient and Versatile Neural Stabilizer for Video Depth Estimation Code
#27SwinV2-L 1K-MIMSOTA
0.949
Delta < 1.25· 2022-05-26
Revealing the Dark Secrets of Masked Image Modeling Code
#28DepthGen
0.946
Delta < 1.25· Augmentations· 2023-02-28
Monocular Depth Estimation using Diffusion Models
#29Metric3D (ConvNeXt-Large, Zero-shot testing)
0.944
Delta < 1.25· Augmentations· 2023-07-20
Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Image Code
#30VA-DepthNet(SwinV1-L)
0.937
Delta < 1.25· 2023-02-13
VA-DepthNet: A Variational Approach to Single Image Depth Prediction Code
#31MIM-Swin-V2
0.9361
Delta < 1.25· 2023-11-07
Analysis of NaN Divergence in Training Monocular Depth Estimation Model
#32NDDepth
0.936
Delta < 1.25· 2023-09-19
NDDepth: Normal-Distance Assisted Monocular Depth Estimation Code
#33IEBins
0.936
Delta < 1.25· 2023-09-25
IEBins: Iterative Elastic Bins for Monocular Depth Estimation Code
#34URCDC-Depth
0.933
Delta < 1.25· 2023-02-16
URCDC-Depth: Uncertainty Rectified Cross-Distillation with CutFlip for Monocular Depth Estimation Code
#35OrdinalEntropy
0.932
Delta < 1.25· 2023-01-21
Improving Deep Regression with Ordinal Entropy Code
#36Gaming for Depth (GfD)
0.931
Delta < 1.25· Augmentations
No paper
#37PixelFormer
0.929
Delta < 1.25· 2022-10-17
Attention Attention Everywhere: Monocular Depth Prediction with Skip Attention Code
#38BinsFormerSOTA
0.925
Delta < 1.25· 2022-04-03
BinsFormer: Revisiting Adaptive Bins for Monocular Depth Estimation Code
#39NeWCRFsSOTA
0.922
Delta < 1.25· 2022-03-03
NeW CRFs: Neural Window Fully-connected CRFs for Monocular Depth Estimation Code
#40DDP (step3)
0.921
Delta < 1.25· 2023-03-30
DDP: Diffusion Model for Dense Visual Prediction Code
#41DepthFormer
0.921
Delta < 1.25· 2022-03-27
DepthFormer: Exploiting Long-Range Correlation and Local Information for Accurate Monocular Depth Estimation Code
#42D-Net
0.919
Delta < 1.25
No paperCode
#43LeReSSOTA
0.916
Delta < 1.25· Augmentations· 2020-12-17
Learning to Recover 3D Scene Shape from a Single Image Code
#44GLPDepth
0.915
Delta < 1.25· 2022-01-19
Global-Local Path Networks for Monocular Depth Estimation with Vertical CutDepth Code
#45Depth-Map-Decomposition-HRWSI
0.913
Delta < 1.25· Augmentations· 2022-08-23
Depth Map Decomposition for Monocular Depth Estimation Code
#46Depthformer
0.913
Delta < 1.25· 2022-07-10
Depthformer : Multiscale Vision Transformer For Monocular Depth Estimation With Local Global Information Fusion Code
#47LocalBins
0.91
Delta < 1.25· 2022-03-28
LocalBins: Improving Depth Estimation by Learning Local Distributions Code
#48IronDepth
0.91
Delta < 1.25· 2022-10-07
IronDepth: Iterative Refinement of Single-View Depth using Surface Normal and its Uncertainty Code
#49Depth-Map-Decomposition
0.907
Delta < 1.25· 2022-08-23
Depth Map Decomposition for Monocular Depth Estimation Code
#50DPT-Hybrid
0.904
Delta < 1.25· Augmentations· 2021-03-24
Vision Transformers for Dense Prediction Code
#51AdaBinsSOTA
0.903
Delta < 1.25· 2020-11-28
AdaBins: Depth Estimation using Adaptive Bins Code
#52CutDepth
0.899
Delta < 1.25· Augmentations· 2021-07-16
CutDepth:Edge-aware Data Augmentation in Depth Estimation Code
#53P3Depth
0.898
Delta < 1.25· 2022-04-05
P3Depth: Monocular Depth Estimation with a Piecewise Planarity Prior Code
#54LapDepth
0.895
Delta < 1.25
No paperCode
#55VNLSOTA
0.875
Delta < 1.25· 2019-07-29
Enforcing geometric constraints of virtual normal for depth prediction Code
#56Focal-WNet
0.875
Delta < 1.25
No paperCode
#57SC-DepthV2
0.82
Delta < 1.25· 2020-06-04
Auto-Rectify Network for Unsupervised Indoor Depth Estimation Code