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Depth Estimation On Nyu Depth V2

المقاييس

RMS

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

اسم النموذج
RMS
Paper TitleRepository
Freeform0.433Deep Optics for Monocular Depth Estimation and 3D Object Detection-
P3Depth0.356P3Depth: Monocular Depth Estimation with a Piecewise Planarity Prior-
PAD-Net0.792PAD-Net: Multi-Tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing-
EVP0.224EVP: Enhanced Visual Perception using Inverse Multi-Attentive Feature Refinement and Regularized Image-Text Alignment-
Optimized, freeform0.4325Deep 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)0.365Transformer-Based Attention Networks for Continuous Pixel-Wise Prediction-
DINOv2 (ViT-g/14 frozen, w/ DPT decoder)0.279DINOv2: Learning Robust Visual Features without Supervision-
AdaBins0.364AdaBins: Depth Estimation using Adaptive Bins-
VNL0.416Enforcing geometric constraints of virtual normal for depth prediction-
SwinV2-B 1K-MIM0.304Revealing the Dark Secrets of Masked Image Modeling-
Semantic-aware NN0.303D Ken Burns Effect from a Single Image-
DORN0.509Deep Ordinal Regression Network for Monocular Depth Estimation-
SwinV2-L 1K-MIM0.287Revealing 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-CRF0.586Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation-
BTS0.407From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation-
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Depth Estimation On Nyu Depth V2 | SOTA | HyperAI