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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

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Showing 151–175 of 876 papers

TitleStatusHype
RePoseD: Efficient Relative Pose Estimation With Known Depth InformationCode1
BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression TasksCode1
Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth EstimationCode1
Depth Estimation from Monocular Images and Sparse radar using Deep Ordinal Regression NetworkCode1
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier ConvolutionsCode1
Frequency-Aware Self-Supervised Monocular Depth EstimationCode1
GasMono: Geometry-Aided Self-Supervised Monocular Depth Estimation for Indoor ScenesCode1
GCNDepth: Self-supervised Monocular Depth Estimation based on Graph Convolutional NetworkCode1
Deep Ordinal Regression Network for Monocular Depth EstimationCode1
BaseBoostDepth: Exploiting Larger Baselines For Self-supervised Monocular Depth EstimationCode1
Deep Two-View Structure-from-Motion RevisitedCode1
DeFeat-Net: General Monocular Depth via Simultaneous Unsupervised Representation LearningCode1
altiro3D: Scene representation from single image and novel view synthesisCode1
GroCo: Ground Constraint for Metric Self-Supervised Monocular DepthCode1
Harnessing Diffusion Models for Visual Perception with Meta PromptsCode1
High Quality Monocular Depth Estimation via Transfer LearningCode1
Global and Hierarchical Geometry Consistency Priors for Few-shot NeRFs in Indoor ScenesCode1
Deeper into Self-Supervised Monocular Indoor Depth EstimationCode1
Depth and DOF Cues Make A Better Defocus Blur DetectorCode1
Depth Any Canopy: Leveraging Depth Foundation Models for Canopy Height EstimationCode1
Deeper Depth Prediction with Fully Convolutional Residual NetworksCode1
Excavating the Potential Capacity of Self-Supervised Monocular Depth EstimationCode1
ENRICH: Multi-purposE dataset for beNchmaRking In Computer vision and pHotogrammetryCode1
Always Clear Depth: Robust Monocular Depth Estimation under Adverse WeatherCode1
EVP: Enhanced Visual Perception using Inverse Multi-Attentive Feature Refinement and Regularized Image-Text AlignmentCode1
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