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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 301–350 of 876 papers

TitleStatusHype
SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry EstimationCode1
Stealing Stable Diffusion Prior for Robust Monocular Depth EstimationCode1
The Monocular Depth Estimation ChallengeCode1
Uni-DVPS: Unified Model for Depth-Aware Video Panoptic SegmentationCode1
Depth Any Canopy: Leveraging Depth Foundation Models for Canopy Height EstimationCode1
Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic ImageryCode0
Consistency Regularisation for Unsupervised Domain Adaptation in Monocular Depth EstimationCode0
Self-Supervised Monocular Depth HintsCode0
Conf-Net: Toward High-Confidence Dense 3D Point-Cloud with Error-Map PredictionCode0
Edge-Guided Occlusion Fading Reduction for a Light-Weighted Self-Supervised Monocular Depth EstimationCode0
Adversarial Manhole: Challenging Monocular Depth Estimation and Semantic Segmentation Models with Patch AttackCode0
EDADepth: Enhanced Data Augmentation for Monocular Depth EstimationCode0
Self-Supervised Monocular Depth Estimation with Self-Reference Distillation and Disparity Offset RefinementCode0
Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion SegmentationCode0
Self-supervised monocular depth estimation from oblique UAV videosCode0
Dual CNN Models for Unsupervised Monocular Depth EstimationCode0
Adversarial Attacks on Monocular Pose EstimationCode0
Self-Supervised Learning based Depth Estimation from Monocular ImagesCode0
ClearGrasp: 3D Shape Estimation of Transparent Objects for ManipulationCode0
On the Viability of Monocular Depth Pre-training for Semantic SegmentationCode0
ScaleDepth: Decomposing Metric Depth Estimation into Scale Prediction and Relative Depth EstimationCode0
D-Net: A Generalised and Optimised Deep Network for Monocular Depth EstimationCode0
SaccadeCam: Adaptive Visual Attention for Monocular Depth SensingCode0
SAFENet: Self-Supervised Monocular Depth Estimation with Semantic-Aware Feature ExtractionCode0
Semi-SD: Semi-Supervised Metric Depth Estimation via Surrounding Cameras for Autonomous DrivingCode0
Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on RegressionCode0
Revisiting Single Image Depth Estimation: Toward Higher Resolution Maps with Accurate Object BoundariesCode0
Revisiting Self-Supervised Monocular Depth EstimationCode0
Digging Into Self-Supervised Monocular Depth EstimationCode0
Camera-Independent Single Image Depth Estimation from Defocus BlurCode0
An Online Adaptation Method for Robust Depth Estimation and Visual Odometry in the Open WorldCode0
Recurrent Scene Parsing with Perspective Understanding in the LoopCode0
Depth Prompting for Sensor-Agnostic Depth EstimationCode0
Progressive Fusion for Unsupervised Binocular Depth Estimation using Cycled NetworksCode0
Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular VideosCode0
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional ArchitectureCode0
Plugging Self-Supervised Monocular Depth into Unsupervised Domain Adaptation for Semantic SegmentationCode0
Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown CamerasCode0
Pose Constraints for Consistent Self-supervised Monocular Depth and Ego-motionCode0
Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric AnnotationsCode0
RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language DescriptionsCode0
DepthFormer: Exploiting Long-Range Correlation and Local Information for Accurate Monocular Depth EstimationCode0
Analysis & Computational Complexity Reduction of Monocular and Stereo Depth Estimation TechniquesCode0
Enhanced Encoder-Decoder Architecture for Accurate Monocular Depth EstimationCode0
Panoramic Depth Estimation via Supervised and Unsupervised Learning in Indoor ScenesCode0
On the Benefit of Adversarial Training for Monocular Depth EstimationCode0
On the Robustness of Language Guidance for Low-Level Vision Tasks: Findings from Depth EstimationCode0
An Adversarial Generative Network Designed for High-Resolution Monocular Depth Estimation from 2D HiRISE Images of MarsCode0
On Robust Cross-View Consistency in Self-Supervised Monocular Depth EstimationCode0
OmniDepth: Dense Depth Estimation for Indoors Spherical PanoramasCode0
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