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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 151–200 of 876 papers

TitleStatusHype
InSpaceType: Dataset and Benchmark for Reconsidering Cross-Space Type Performance in Indoor Monocular DepthCode1
LiteDepth: Digging into Fast and Accurate Depth Estimation on Mobile DevicesCode1
HSPFormer: Hierarchical Spatial Perception Transformer for Semantic SegmentationCode1
HR-Depth: High Resolution Self-Supervised Monocular Depth EstimationCode1
High Quality Monocular Depth Estimation via Transfer LearningCode1
Detaching and Boosting: Dual Engine for Scale-Invariant Self-Supervised Monocular Depth EstimationCode1
Holopix50k: A Large-Scale In-the-wild Stereo Image DatasetCode1
GroCo: Ground Constraint for Metric Self-Supervised Monocular DepthCode1
BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression TasksCode1
Guiding Monocular Depth Estimation Using Depth-Attention VolumeCode1
Deep Two-View Structure-from-Motion RevisitedCode1
DeFeat-Net: General Monocular Depth via Simultaneous Unsupervised Representation LearningCode1
Global-Local Path Networks for Monocular Depth Estimation with Vertical CutDepthCode1
Detecting Invisible PeopleCode1
Implicit Integration of Superpixel Segmentation into Fully Convolutional NetworksCode1
Improving 360 Monocular Depth Estimation via Non-local Dense Prediction Transformer and Joint Supervised and Self-supervised LearningCode1
Gradient-based Uncertainty for Monocular Depth EstimationCode1
InSpaceType: Reconsider Space Type in Indoor Monocular Depth EstimationCode1
Depth and DOF Cues Make A Better Defocus Blur DetectorCode1
Depth Any Canopy: Leveraging Depth Foundation Models for Canopy Height EstimationCode1
Harnessing Diffusion Models for Visual Perception with Meta PromptsCode1
Deeper into Self-Supervised Monocular Indoor Depth EstimationCode1
Deeper Depth Prediction with Fully Convolutional Residual NetworksCode1
Always Clear Depth: Robust Monocular Depth Estimation under Adverse WeatherCode1
GEDepth: Ground Embedding for Monocular Depth EstimationCode1
Digging Into Uncertainty-based Pseudo-label for Robust Stereo MatchingCode1
Depth Attention for Robust RGB TrackingCode1
BodySLAM: A Generalized Monocular Visual SLAM Framework for Surgical ApplicationsCode1
GasMono: Geometry-Aided Self-Supervised Monocular Depth Estimation for Indoor ScenesCode1
Learning Depth Estimation for Transparent and Mirror SurfacesCode1
Learning Occlusion-Aware Coarse-to-Fine Depth Map for Self-supervised Monocular Depth EstimationCode1
DELTAS: Depth Estimation by Learning Triangulation And densification of Sparse pointsCode1
Depth Estimation from Monocular Images and Sparse radar using Deep Ordinal Regression NetworkCode1
Boosting Light-Weight Depth Estimation Via Knowledge DistillationCode1
From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth EstimationCode1
Digging Into Self-Supervised Monocular Depth EstimationCode1
GCNDepth: Self-supervised Monocular Depth Estimation based on Graph Convolutional NetworkCode1
RePoseD: Efficient Relative Pose Estimation With Known Depth InformationCode1
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier ConvolutionsCode1
Depthformer : Multiscale Vision Transformer For Monocular Depth Estimation With Local Global Information FusionCode1
Deconstructing Self-Supervised Monocular Reconstruction: The Design Decisions that MatterCode1
A geometry-aware deep network for depth estimation in monocular endoscopyCode1
Frequency-Aware Self-Supervised Monocular Depth EstimationCode1
M4Depth: Monocular depth estimation for autonomous vehicles in unseen environmentsCode1
DepthLab: Real-Time 3D Interaction With Depth Maps for Mobile Augmented RealityCode1
Depth Map Decomposition for Monocular Depth EstimationCode1
Depth Map Prediction from a Single Image using a Multi-Scale Deep NetworkCode1
Global and Hierarchical Geometry Consistency Priors for Few-shot NeRFs in Indoor ScenesCode1
3DPPE: 3D Point Positional Encoding for Multi-Camera 3D Object Detection TransformersCode1
IEBins: Iterative Elastic Bins for Monocular Depth EstimationCode1
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