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الرئيسية
SOTA
Depth Estimation
Depth Estimation On Nyu Depth V2
Depth Estimation On Nyu Depth V2
المقاييس
RMS
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
RMS
Paper Title
Repository
Freeform
0.433
Deep Optics for Monocular Depth Estimation and 3D Object Detection
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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
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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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