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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 201–225 of 876 papers

TitleStatusHype
Multi-Loss Rebalancing Algorithm for Monocular Depth EstimationCode1
Multi-Loss Weighting with Coefficient of VariationsCode1
EC-Depth: Exploring the consistency of self-supervised monocular depth estimation in challenging scenesCode1
NDDepth: Normal-Distance Assisted Monocular Depth Estimation and CompletionCode1
Deconstructing Self-Supervised Monocular Reconstruction: The Design Decisions that MatterCode1
A geometry-aware deep network for depth estimation in monocular endoscopyCode1
Gradient-based Uncertainty for Monocular Depth EstimationCode1
High Quality Monocular Depth Estimation via Transfer LearningCode1
Detaching and Boosting: Dual Engine for Scale-Invariant Self-Supervised Monocular Depth EstimationCode1
Detecting Invisible PeopleCode1
A benchmark with decomposed distribution shifts for 360 monocular depth estimationCode1
Kick Back & Relax: Learning to Reconstruct the World by Watching SlowTVCode1
GCNDepth: Self-supervised Monocular Depth Estimation based on Graph Convolutional NetworkCode1
GEDepth: Ground Embedding for Monocular Depth EstimationCode1
DCDepth: Progressive Monocular Depth Estimation in Discrete Cosine DomainCode1
Advancing Self-supervised Monocular Depth Learning with Sparse LiDARCode1
Digging Into Uncertainty-based Pseudo-label for Robust Stereo MatchingCode1
Aerial Single-View Depth Completion with Image-Guided Uncertainty EstimationCode1
GasMono: Geometry-Aided Self-Supervised Monocular Depth Estimation for Indoor ScenesCode1
Physical Attack on Monocular Depth Estimation with Optimal Adversarial PatchesCode1
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier ConvolutionsCode1
PlaneDepth: Self-supervised Depth Estimation via Orthogonal PlanesCode1
DaRF: Boosting Radiance Fields from Sparse Inputs with Monocular Depth AdaptationCode1
Frequency-Aware Self-Supervised Monocular Depth EstimationCode1
DARES: Depth Anything in Robotic Endoscopic Surgery with Self-supervised Vector-LoRA of the Foundation ModelCode1
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