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Monocular Depth Estimation

Monocular Depth Estimation is the task of estimating the depth value (distance relative to the camera) of each pixel given a single (monocular) RGB image. This challenging task is a key prerequisite for determining scene understanding for applications such as 3D scene reconstruction, autonomous driving, and AR. State-of-the-art methods usually fall into one of two categories: designing a complex network that is powerful enough to directly regress the depth map, or splitting the input into bins or windows to reduce computational complexity. The most popular benchmarks are the KITTI and NYUv2 datasets. Models are typically evaluated using RMSE or absolute relative error.

Source: Defocus Deblurring Using Dual-Pixel Data

Papers

Showing 276300 of 876 papers

TitleStatusHype
EVP: Enhanced Visual Perception using Inverse Multi-Attentive Feature Refinement and Regularized Image-Text AlignmentCode1
Excavating the Potential Capacity of Self-Supervised Monocular Depth EstimationCode1
Learning Occlusion-Aware Coarse-to-Fine Depth Map for Self-supervised Monocular Depth EstimationCode1
Aerial Single-View Depth Completion with Image-Guided Uncertainty EstimationCode1
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier ConvolutionsCode1
DCDepth: Progressive Monocular Depth Estimation in Discrete Cosine DomainCode1
Learning to Upsample by Learning to SampleCode1
Image Masking for Robust Self-Supervised Monocular Depth EstimationCode1
From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth EstimationCode1
EndoMUST: Monocular Depth Estimation for Robotic Endoscopy via End-to-end Multi-step Self-supervised TrainingCode1
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary CellsCode1
HR-Depth: High Resolution Self-Supervised Monocular Depth EstimationCode1
GasMono: Geometry-Aided Self-Supervised Monocular Depth Estimation for Indoor ScenesCode1
HSPFormer: Hierarchical Spatial Perception Transformer for Semantic SegmentationCode1
M4Depth: Monocular depth estimation for autonomous vehicles in unseen environmentsCode1
Feature-metric Loss for Self-supervised Learning of Depth and EgomotionCode1
Metrically Scaled Monocular Depth Estimation through Sparse Priors for Underwater RobotsCode1
MGNet: Monocular Geometric Scene Understanding for Autonomous DrivingCode1
Mind The Edge: Refining Depth Edges in Sparsely-Supervised Monocular Depth EstimationCode1
Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth EstimationCode1
EndoDepth: A Benchmark for Assessing Robustness in Endoscopic Depth PredictionCode1
Monocular Depth Estimation through Virtual-world Supervision and Real-world SfM Self-SupervisionCode1
Monocular Depth Estimation Using Laplacian Pyramid-Based Depth ResidualsCode1
RePoseD: Efficient Relative Pose Estimation With Known Depth InformationCode1
A technique to jointly estimate depth and depth uncertainty for unmanned aerial vehiclesCode1
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