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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 201–250 of 876 papers

TitleStatusHype
Learning a Geometric Representation for Data-Efficient Depth Estimation via Gradient Field and Contrastive LossCode1
Learning Depth Estimation for Transparent and Mirror SurfacesCode1
Learning Occlusion-Aware Coarse-to-Fine Depth Map for Self-supervised Monocular Depth EstimationCode1
Revealing the Dark Secrets of Masked Image ModelingCode1
Out-of-Distribution Detection for Monocular Depth EstimationCode1
OceanLens: An Adaptive Backscatter and Edge Correction using Deep Learning Model for Enhanced Underwater ImagingCode1
OmniFusion: 360 Monocular Depth Estimation via Geometry-Aware FusionCode1
Learning Stereo from Single ImagesCode1
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
Deconstructing Self-Supervised Monocular Reconstruction: The Design Decisions that MatterCode1
A geometry-aware deep network for depth estimation in monocular endoscopyCode1
Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth EstimationCode1
One Shot 3D PhotographyCode1
Advancing Self-supervised Monocular Depth Learning with Sparse LiDARCode1
Digging Into Uncertainty-based Pseudo-label for Robust Stereo MatchingCode1
Overcoming the Distance Estimation Bottleneck in Estimating Animal Abundance with Camera TrapsCode1
DiPE: Deeper into Photometric Errors for Unsupervised Learning of Depth and Ego-motion from Monocular VideosCode1
EVP: Enhanced Visual Perception using Inverse Multi-Attentive Feature Refinement and Regularized Image-Text AlignmentCode1
LightedDepth: Video Depth Estimation in Light of Limited Inference View AnglesCode1
Lightweight Monocular Depth Estimation through Guided DecodingCode1
Excavating the Potential Capacity of Self-Supervised Monocular Depth EstimationCode1
DCDepth: Progressive Monocular Depth Estimation in Discrete Cosine DomainCode1
Aerial Single-View Depth Completion with Image-Guided Uncertainty EstimationCode1
Distilled Semantics for Comprehensive Scene Understanding from VideosCode1
ENRICH: Multi-purposE dataset for beNchmaRking In Computer vision and pHotogrammetryCode1
M4Depth: Monocular depth estimation for autonomous vehicles in unseen environmentsCode1
A Practical Stereo Depth System for Smart GlassesCode1
NDDepth: Normal-Distance Assisted Monocular Depth Estimation and CompletionCode1
EndoMUST: Monocular Depth Estimation for Robotic Endoscopy via End-to-end Multi-step Self-supervised TrainingCode1
DaRF: Boosting Radiance Fields from Sparse Inputs with Monocular Depth AdaptationCode1
Manydepth2: Motion-Aware Self-Supervised Multi-Frame Monocular Depth Estimation in Dynamic ScenesCode1
Monocular Depth Distribution Alignment with Low ComputationCode1
Mind The Edge: Refining Depth Edges in Sparsely-Supervised Monocular Depth EstimationCode1
Self-Supervised Learning for Monocular Depth Estimation from Aerial ImageryCode1
CoDEPS: Online Continual Learning for Depth Estimation and Panoptic SegmentationCode1
Mining Supervision for Dynamic Regions in Self-Supervised Monocular Depth EstimationCode1
DARES: Depth Anything in Robotic Endoscopic Surgery with Self-supervised Vector-LoRA of the Foundation ModelCode1
A Study on Self-Supervised Pretraining for Vision Problems in Gastrointestinal EndoscopyCode1
Multi-Loss Weighting with Coefficient of VariationsCode1
Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth PredictionCode1
Dyna-DM: Dynamic Object-aware Self-supervised Monocular Depth MapsCode1
A Study on the Generality of Neural Network Structures for Monocular Depth EstimationCode1
EC-Depth: Exploring the consistency of self-supervised monocular depth estimation in challenging scenesCode1
Multi-resolution Monocular Depth Map Fusion by Self-supervised Gradient-based CompositionCode1
Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce ModelCode1
Self-Supervised Monocular Scene Flow EstimationCode1
NDDepth: Normal-Distance Assisted Monocular Depth EstimationCode1
NVDS+: Towards Efficient and Versatile Neural Stabilizer for Video Depth EstimationCode1
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