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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 101–125 of 876 papers

TitleStatusHype
Enhancing Bronchoscopy Depth Estimation through Synthetic-to-Real Domain Adaptation—0
PMPNet: Pixel Movement Prediction Network for Monocular Depth Estimation in Dynamic Scenes—0
Improving Domain Generalization in Self-supervised Monocular Depth Estimation via Stabilized Adversarial Training—0
Optical Lens Attack on Monocular Depth Estimation for Autonomous Driving—0
ImOV3D: Learning Open-Vocabulary Point Clouds 3D Object Detection from Only 2D ImagesCode2
PF3plat: Pose-Free Feed-Forward 3D Gaussian SplattingCode3
Depth Attention for Robust RGB TrackingCode1
Thermal Chameleon: Task-Adaptive Tone-mapping for Radiometric Thermal-Infrared imagesCode1
DCDepth: Progressive Monocular Depth Estimation in Discrete Cosine DomainCode1
Enhanced Encoder-Decoder Architecture for Accurate Monocular Depth EstimationCode0
Surgical Depth Anything: Depth Estimation for Surgical Scenes using Foundation Models—0
Structure-Centric Robust Monocular Depth Estimation via Knowledge Distillation—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
Refinement of Monocular Depth Maps via Multi-View Differentiable RenderingCode2
RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language DescriptionsCode0
Depth Pro: Sharp Monocular Metric Depth in Less Than a SecondCode9
EndoDepth: A Benchmark for Assessing Robustness in Endoscopic Depth PredictionCode1
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
EventHDR: from Event to High-Speed HDR Videos and Beyond—0
Parameter-efficient Bayesian Neural Networks for Uncertainty-aware Depth Estimation—0
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