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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

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Showing 601–625 of 876 papers

TitleStatusHype
Mono2Stereo: Monocular Knowledge Transfer for Enhanced Stereo Matching—0
Monocular Depth Estimation: A Survey—0
Monocular Depth Estimation Based On Deep Learning: An Overview—0
Monocular Depth Estimation by Learning from Heterogeneous Datasets—0
Monocular Depth Estimation for Soft Visuotactile Sensors—0
Monocular Depth Estimation Primed by Salient Point Detection and Normalized Hessian Loss—0
Monocular Depth Estimation using Diffusion Models—0
Monocular Depth Estimation Using Multi Scale Neural Network And Feature Fusion—0
Monocular Depth Estimation Using Neural Regression Forest—0
Monocular Depth Estimation Using Relative Depth Maps—0
Monocular Depth Estimation Using Whole Strip Masking and Reliability-Based Refinement—0
Monocular Depth Estimation with Affinity, Vertical Pooling, and Label Enhancement—0
Monocular Depth Estimation with Augmented Ordinal Depth Relationships—0
Monocular Depth Estimation with Directional Consistency by Deep Networks—0
Monocular Depth Estimation with Self-supervised Instance Adaptation—0
Monocular Depth Estimation with Sharp Boundary—0
Monocular Depth Estimators: Vulnerabilities and Attacks—0
Monocular Differentiable Rendering for Self-Supervised 3D Object Detection—0
Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping—0
Monocular Piecewise Depth Estimation in Dynamic Scenes by Exploiting Superpixel Relations—0
MonoDVPS: A Self-Supervised Monocular Depth Estimation Approach to Depth-aware Video Panoptic Segmentation—0
MonoIndoor++:Towards Better Practice of Self-Supervised Monocular Depth Estimation for Indoor Environments—0
MonoIndoor: Towards Good Practice of Self-Supervised Monocular Depth Estimation for Indoor Environments—0
MonoPCC: Photometric-invariant Cycle Constraint for Monocular Depth Estimation of Endoscopic Images—0
MonoPP: Metric-Scaled Self-Supervised Monocular Depth Estimation by Planar-Parallax Geometry in Automotive Applications—0
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