Papers with Code · CC BY-SA 4.0

NYU-Depth V2

아카이브 평가 85건 · 마지막 적재/변경 2026-10-30

평가 기록

과거 수집 기록이며 최신 순위가 아닙니다. 데이터셋 버전·split·실험 조건과 지표 방향이 검증되지 않은 결과는 직접 비교할 수 없습니다. 날짜는 논문 날짜이며 최신 평가일을 뜻하지 않습니다.

표가 화면보다 넓으면 좌우로 스크롤하여 논문과 구현 링크를 확인하세요.

원본 기록 순서 · 순위 미부여
모델	원본 지표·값	논문	구현
VA-DepthNet(SwinV1-L)	RMSE 0.304 absolute relative error 0.086 Delta < 1.25 0.937 Delta < 1.25^2 0.992 Delta < 1.25^3 0.999 log 10 0.037	VA-DepthNet: A Variational Approach to Single Image Depth Prediction 2023-02-13	코드 1 · 코드 2
iDisc	absolute relative error 0.086 Delta < 1.25^2 0.993 Delta < 1.25^3 0.999	iDisc: Internal Discretization for Monocular Depth Estimation 2023-04-13	코드 1 · 코드 2
MIM-Swin-V2	RMSE 0.3046 absolute relative error 0.0864 Delta < 1.25 0.9361 Delta < 1.25^2 0.9916 Delta < 1.25^3 0.9981 log 10 0.0365	Analysis of NaN Divergence in Training Monocular Depth Estimation Model 2023-11-07	연결 없음
NDDepth	RMSE 0.311 absolute relative error 0.087 Delta < 1.25 0.936 Delta < 1.25^2 0.991 Delta < 1.25^3 0.998 log 10 0.038	NDDepth: Normal-Distance Assisted Monocular Depth Estimation 2023-09-19	코드 1
IEBins	RMSE 0.314 absolute relative error 0.087 Delta < 1.25 0.936 Delta < 1.25^2 0.992 Delta < 1.25^3 0.998 log 10 0.038	IEBins: Iterative Elastic Bins for Monocular Depth Estimation 2023-09-25	코드 1
URCDC-Depth	RMSE 0.316 absolute relative error 0.088 Delta < 1.25 0.933 Delta < 1.25^2 0.992 Delta < 1.25^3 0.998 log 10 0.038	URCDC-Depth: Uncertainty Rectified Cross-Distillation with CutFlip for Monocular Depth Estimation 2023-02-16	코드 1
OrdinalEntropy	RMSE 0.321 absolute relative error 0.089 Delta < 1.25 0.932 log 10 0.039	Improving Deep Regression with Ordinal Entropy 2023-01-21	코드 1
PixelFormer	RMSE 0.322 absolute relative error 0.090 Delta < 1.25 0.929 Delta < 1.25^2 0.991 Delta < 1.25^3 0.998 log 10 0.039	Attention Attention Everywhere: Monocular Depth Prediction with Skip Attention 2022-10-17	코드 1
LeReS	absolute relative error 0.09 Delta < 1.25 0.916	Learning to Recover 3D Scene Shape from a Single Image 2020-12-17	코드 1
DINOv2 (ViT-g/14 frozen, w/ DPT decoder)	RMSE 0.279 absolute relative error 0.0907 Delta < 1.25 0.9497 Delta < 1.25^2 0.996 Delta < 1.25^3 0.9994 log 10 0.0371	DINOv2: Learning Robust Visual Features without Supervision 2023-04-14	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 · 코드 10 · 코드 11 · 코드 12 · 코드 13 · 코드 14 · 코드 15 · 코드 16 · 코드 17 · 코드 18 · 코드 19 · 코드 20 · 코드 21 · 코드 22 · 코드 23 · 코드 24 · 코드 25 · 코드 26
DDP (step3)	RMSE 0.329 absolute relative error 0.094 Delta < 1.25 0.921 Delta < 1.25^2 0.990 Delta < 1.25^3 0.998 log 10 0.040	DDP: Diffusion Model for Dense Visual Prediction 2023-03-30	코드 1
BinsFormer	RMSE 0.330 absolute relative error 0.094 Delta < 1.25 0.925 Delta < 1.25^2 0.989 Delta < 1.25^3 0.997 log 10 0.040	BinsFormer: Revisiting Adaptive Bins for Monocular Depth Estimation 2022-04-03	코드 1 · 코드 2
NeWCRFs	RMSE 0.334 absolute relative error 0.095 Delta < 1.25 0.922 Delta < 1.25^2 0.992 Delta < 1.25^3 0.998 log 10 0.041	NeW CRFs: Neural Window Fully-connected CRFs for Monocular Depth Estimation 2022-03-03	코드 1
D-Net	RMSE 0.354 absolute relative error 0.095 Delta < 1.25 0.919 Delta < 1.25^2 0.988 Delta < 1.25^3 0.997 log 10 0.041	D-Net: A Generalised and Optimised Deep Network for Monocular Depth Estimation 2021-09-29	코드 1
DepthFormer	RMSE 0.339 absolute relative error 0.096 Delta < 1.25 0.921 Delta < 1.25^2 0.989 Delta < 1.25^3 0.998 log 10 0.041	DepthFormer: Exploiting Long-Range Correlation and Local Information for Accurate Monocular Depth Estimation 2022-03-27	코드 1
GLPDepth	RMSE 0.344 absolute relative error 0.098 Delta < 1.25 0.915 Delta < 1.25^2 0.988 Delta < 1.25^3 0.997 log 10 0.042	Global-Local Path Networks for Monocular Depth Estimation with Vertical CutDepth 2022-01-19	코드 1 · 코드 2 · 코드 3 · 코드 4
LocalBins	RMSE 0.351 absolute relative error 0.098 Delta < 1.25 0.91 Delta < 1.25^2 0.986 Delta < 1.25^3 0.997 log 10 0.042	LocalBins: Improving Depth Estimation by Learning Local Distributions 2022-03-28	코드 1
Depth-Map-Decomposition-HRWSI	RMSE 0.355 absolute relative error 0.098 Delta < 1.25 0.913 Delta < 1.25^2 0.987 Delta < 1.25^3 0.998 log 10 0.042	Depth Map Decomposition for Monocular Depth Estimation 2022-08-23	코드 1
Depthformer	RMSE 0.345 absolute relative error 0.100 Delta < 1.25 0.913 Delta < 1.25^2 0.988 Delta < 1.25^3 0.997 log 10 0.042	Depthformer : Multiscale Vision Transformer For Monocular Depth Estimation With Local Global Information Fusion 2022-07-10	코드 1
Depth-Map-Decomposition	RMSE 0.362 absolute relative error 0.100 Delta < 1.25 0.907 Delta < 1.25^2 0.986 Delta < 1.25^3 0.997 log 10 0.043	Depth Map Decomposition for Monocular Depth Estimation 2022-08-23	코드 1
IronDepth	RMSE 0.352 absolute relative error 0.101 Delta < 1.25 0.910 Delta < 1.25^2 0.985 Delta < 1.25^3 0.997 log 10 0.043	IronDepth: Iterative Refinement of Single-View Depth using Surface Normal and its Uncertainty 2022-10-07	코드 1
AdaBins	RMSE 0.364 absolute relative error 0.103 Delta < 1.25 0.903 Delta < 1.25^2 0.984 Delta < 1.25^3 0.997 log 10 0.044	AdaBins: Depth Estimation using Adaptive Bins 2020-11-28	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 · 코드 10 · 코드 11
P3Depth	RMSE 0.356 absolute relative error 0.104 Delta < 1.25 0.898 Delta < 1.25^2 0.981 Delta < 1.25^3 0.996 log 10 0.043	P3Depth: Monocular Depth Estimation with a Piecewise Planarity Prior 2022-04-05	코드 1
CutDepth	RMSE 0.375 absolute relative error 0.104 Delta < 1.25 0.899 Delta < 1.25^2 0.985 Delta < 1.25^3 0.997 log 10 0.044	CutDepth:Edge-aware Data Augmentation in Depth Estimation 2021-07-16	코드 1
LapDepth	RMSE 0.384 absolute relative error 0.105 Delta < 1.25 0.895 Delta < 1.25^2 0.983 Delta < 1.25^3 0.996 log 10 0.045	Monocular Depth Estimation Using Laplacian Pyramid-Based Depth Residuals 2021-01-08	코드 1
DPT-Hybrid	RMSE 0.357 absolute relative error 0.110 Delta < 1.25 0.904 Delta < 1.25^2 0.988 Delta < 1.25^3 0.994 log 10 0.045	Vision Transformers for Dense Prediction 2021-03-24	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 · 코드 10 · 코드 11 · 코드 12 · 코드 13 · 코드 14 · 코드 15
VNL	RMSE 0.416 absolute relative error 0.111 Delta < 1.25 0.875 Delta < 1.25^2 0.976 Delta < 1.25^3 0.989 log 10 0.048	Enforcing geometric constraints of virtual normal for depth prediction 2019-07-29	코드 1 · 코드 2 · 코드 3
Focal-WNet	RMSE 0.398 absolute relative error 0.116 Delta < 1.25 0.875 Delta < 1.25^2 0.980 Delta < 1.25^3 0.995 log 10 0.048	Focal-WNet: An Architecture Unifying Convolution and Attention for Depth Estimation 2022-07-18	코드 1
SC-DepthV2	RMSE 0.532 absolute relative error 0.138 Delta < 1.25 0.820 Delta < 1.25^2 0.956 log 10 0.059	Auto-Rectify Network for Unsupervised Indoor Depth Estimation 2020-06-04	코드 1
NVS-MonoDepth	RMSE 0.331	NVS-MonoDepth: Improving Monocular Depth Prediction with Novel View Synthesis 2021-12-22	연결 없음