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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 751–775 of 876 papers

TitleStatusHype
Dense monocular Simultaneous Localization and Mapping by direct surfel optimization—0
FIS-Nets: Full-image Supervised Networks for Monocular Depth Estimation—0
Perception and Navigation in Autonomous Systems in the Era of Learning: A Survey—0
Don't Forget The Past: Recurrent Depth Estimation from Monocular Video—0
Edge-Guided Occlusion Fading Reduction for a Light-Weighted Self-Supervised Monocular Depth EstimationCode0
Analysis of Deep Networks for Monocular Depth Estimation Through Adversarial Attacks with Proposal of a Defense Method—0
On the Benefit of Adversarial Training for Monocular Depth EstimationCode0
Deep Classification Network for Monocular Depth Estimation—0
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments—0
Unsupervised High-Resolution Depth Learning From Videos With Dual Networks—0
ClearGrasp: 3D Shape Estimation of Transparent Objects for ManipulationCode0
Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances—0
Deep 3D Pan via adaptive "t-shaped" convolutions with global and local adaptive dilations—0
Digging Into Self-Supervised Monocular Depth EstimationCode0
Monocular Piecewise Depth Estimation in Dynamic Scenes by Exploiting Superpixel Relations—0
Deep Depth From Aberration Map—0
Self-Supervised Monocular Depth HintsCode0
Task-Aware Monocular Depth Estimation for 3D Object DetectionCode0
Progressive Fusion for Unsupervised Binocular Depth Estimation using Cycled NetworksCode0
Structure-Attentioned Memory Network for Monocular Depth Estimation—0
Improving Self-Supervised Single View Depth Estimation by Masking OcclusionCode0
UASOL, a large-scale high-resolution outdoor stereo dataset—0
n-MeRCI: A new Metric to Evaluate the Correlation Between Predictive Uncertainty and True Error—0
Structured Coupled Generative Adversarial Networks for Unsupervised Monocular Depth Estimation—0
To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation—0
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