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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 376–400 of 876 papers

TitleStatusHype
MonoPP: Metric-Scaled Self-Supervised Monocular Depth Estimation by Planar-Parallax Geometry in Automotive Applications—0
Spatially Visual Perception for End-to-End Robotic Learning—0
PriorDiffusion: Leverage Language Prior in Diffusion Models for Monocular Depth Estimation—0
MGNiceNet: Unified Monocular Geometric Scene UnderstandingCode0
Scalable Autoregressive Monocular Depth Estimation—0
MetricGold: Leveraging Text-To-Image Latent Diffusion Models for Metric Depth EstimationCode0
Mono2Stereo: Monocular Knowledge Transfer for Enhanced Stereo Matching—0
D^3epth: Self-Supervised Depth Estimation with Dynamic Mask in Dynamic ScenesCode0
Enhancing Bronchoscopy Depth Estimation through Synthetic-to-Real Domain Adaptation—0
Improving Domain Generalization in Self-supervised Monocular Depth Estimation via Stabilized Adversarial Training—0
PMPNet: Pixel Movement Prediction Network for Monocular Depth Estimation in Dynamic Scenes—0
Optical Lens Attack on Monocular Depth Estimation for Autonomous Driving—0
Enhanced Encoder-Decoder Architecture for Accurate Monocular Depth EstimationCode0
Structure-Centric Robust Monocular Depth Estimation via Knowledge Distillation—0
Surgical Depth Anything: Depth Estimation for Surgical Scenes using Foundation Models—0
Vision Transformer based Random Walk for Group Re-Identification—0
EndoPerfect: High-Accuracy Monocular Depth Estimation and 3D Reconstruction for Endoscopic Surgery via NeRF-Stereo Fusion—0
RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language DescriptionsCode0
KineDepth: Utilizing Robot Kinematics for Online Metric Depth Estimation—0
fCOP: Focal Length Estimation from Category-level Object Priors—0
ViewpointDepth: A New Dataset for Monocular Depth Estimation Under Viewpoint Shifts—0
Self-supervised Monocular Depth Estimation with Large Kernel Attention—0
Optical Lens Attack on Deep Learning Based Monocular Depth Estimation—0
Parameter-efficient Bayesian Neural Networks for Uncertainty-aware Depth Estimation—0
EventHDR: from Event to High-Speed HDR Videos and Beyond—0
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