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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 251–275 of 876 papers

TitleStatusHype
Predicting Sharp and Accurate Occlusion Boundaries in Monocular Depth Estimation Using Displacement FieldsCode1
Three Ways to Improve Semantic Segmentation with Self-Supervised Depth EstimationCode1
OceanLens: An Adaptive Backscatter and Edge Correction using Deep Learning Model for Enhanced Underwater ImagingCode1
Toward Practical Monocular Indoor Depth EstimationCode1
Prompt Guided Transformer for Multi-Task Dense PredictionCode1
Photon-Starved Scene Inference using Single Photon CamerasCode1
3D Packing for Self-Supervised Monocular Depth EstimationCode1
Physical Attack on Monocular Depth Estimation with Optimal Adversarial PatchesCode1
CutDepth:Edge-aware Data Augmentation in Depth EstimationCode1
P^2Net: Patch-match and Plane-regularization for Unsupervised Indoor Depth EstimationCode1
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary CellsCode1
Attention Attention Everywhere: Monocular Depth Prediction with Skip AttentionCode1
Feature-metric Loss for Self-supervised Learning of Depth and EgomotionCode1
P3Depth: Monocular Depth Estimation with a Piecewise Planarity PriorCode1
Pixel-Pair Occlusion Relationship Map(P2ORM): Formulation, Inference & ApplicationCode1
Overcoming the Distance Estimation Bottleneck in Estimating Animal Abundance with Camera TrapsCode1
ENRICH: Multi-purposE dataset for beNchmaRking In Computer vision and pHotogrammetryCode1
Adversarial Training of Self-supervised Monocular Depth Estimation against Physical-World AttacksCode1
Excavating the Potential Capacity of Self-Supervised Monocular Depth EstimationCode1
Cross-modal transformers for infrared and visible image fusionCode1
On the uncertainty of self-supervised monocular depth estimationCode1
Atlantis: Enabling Underwater Depth Estimation with Stable DiffusionCode1
Learning to Upsample by Learning to SampleCode1
RePoseD: Efficient Relative Pose Estimation With Known Depth InformationCode1
EndoMUST: Monocular Depth Estimation for Robotic Endoscopy via End-to-end Multi-step Self-supervised TrainingCode1
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