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SOTA
Depth Estimation
Depth Estimation On Nyu Depth V2
Depth Estimation On Nyu Depth V2
평가 지표
RMS
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
RMS
Paper Title
Repository
Freeform
0.433
Deep Optics for Monocular Depth Estimation and 3D Object Detection
-
P3Depth
0.356
P3Depth: Monocular Depth Estimation with a Piecewise Planarity Prior
PAD-Net
0.792
PAD-Net: Multi-Tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing
-
EVP
0.224
EVP: Enhanced Visual Perception using Inverse Multi-Attentive Feature Refinement and Regularized Image-Text Alignment
Optimized, freeform
0.4325
Deep Optics for Monocular Depth Estimation and 3D Object Detection
-
Defocus/DepthNet (Normalized)
-
Focus on defocus: bridging the synthetic to real domain gap for depth estimation
-
TransDepth (AGD+ ViT)
0.365
Transformer-Based Attention Networks for Continuous Pixel-Wise Prediction
DINOv2 (ViT-g/14 frozen, w/ DPT decoder)
0.279
DINOv2: Learning Robust Visual Features without Supervision
AdaBins
0.364
AdaBins: Depth Estimation using Adaptive Bins
VNL
0.416
Enforcing geometric constraints of virtual normal for depth prediction
SwinV2-B 1K-MIM
0.304
Revealing the Dark Secrets of Masked Image Modeling
Semantic-aware NN
0.30
3D Ken Burns Effect from a Single Image
DORN
0.509
Deep Ordinal Regression Network for Monocular Depth Estimation
SwinV2-L 1K-MIM
0.287
Revealing the Dark Secrets of Masked Image Modeling
A2J
-
A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation from a Single Depth Image
MS-CRF
0.586
Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation
BTS
0.407
From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation
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