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الرئيسية
SOTA
تقدير العمق
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
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PAD-Net
0.792
PAD-Net: Multi-Tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing
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EVP
0.224
EVP: Enhanced Visual Perception using Inverse Multi-Attentive Feature Refinement and Regularized Image-Text Alignment
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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
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DINOv2 (ViT-g/14 frozen, w/ DPT decoder)
0.279
DINOv2: Learning Robust Visual Features without Supervision
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AdaBins
0.364
AdaBins: Depth Estimation using Adaptive Bins
-
VNL
0.416
Enforcing geometric constraints of virtual normal for depth prediction
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SwinV2-B 1K-MIM
0.304
Revealing the Dark Secrets of Masked Image Modeling
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Semantic-aware NN
0.30
3D Ken Burns Effect from a Single Image
-
DORN
0.509
Deep Ordinal Regression Network for Monocular Depth Estimation
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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
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MS-CRF
0.586
Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation
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BTS
0.407
From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation
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