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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 1–50 of 876 papers

TitleStatusHype
Vision-based Perception for Autonomous Vehicles in Obstacle Avoidance Scenarios—0
MonoMVSNet: Monocular Priors Guided Multi-View Stereo NetworkCode1
ByDeWay: Boost Your multimodal LLM with DEpth prompting in a Training-Free Way—0
LighthouseGS: Indoor Structure-aware 3D Gaussian Splatting for Panorama-Style Mobile Captures—0
Beyond Appearance: Geometric Cues for Robust Video Instance Segmentation—0
Underwater Monocular Metric Depth Estimation: Real-World Benchmarks and Synthetic Fine-Tuning—0
THIRDEYE: Cue-Aware Monocular Depth Estimation via Brain-Inspired Multi-Stage Fusion—0
Look to Locate: Vision-Based Multisensory Navigation with 3-D Digital Maps for GNSS-Challenged Environments—0
BulletGen: Improving 4D Reconstruction with Bullet-Time Generation—0
Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping—0
EndoMUST: Monocular Depth Estimation for Robotic Endoscopy via End-to-end Multi-step Self-supervised TrainingCode1
TR2M: Transferring Monocular Relative Depth to Metric Depth with Language Descriptions and Scale-Oriented ContrastCode1
EgoM2P: Egocentric Multimodal Multitask Pretraining—0
Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images—0
Jamais Vu: Exposing the Generalization Gap in Supervised Semantic Correspondence—0
Structure-Aware Radar-Camera Depth Estimation—0
Toward Better SSIM Loss for Unsupervised Monocular Depth Estimation—0
Bridging Geometric and Semantic Foundation Models for Generalized Monocular Depth Estimation—0
Spatial RoboGrasp: Generalized Robotic Grasping Control Policy—0
From Single Images to Motion Policies via Video-Generation Environment Representations—0
BadDepth: Backdoor Attacks Against Monocular Depth Estimation in the Physical World—0
DB3D-L: Depth-aware BEV Feature Transformation for Accurate 3D Lane Detection—0
Always Clear Depth: Robust Monocular Depth Estimation under Adverse WeatherCode1
Depth Anything with Any Prior—0
Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image AnalysisCode7
Boosting Zero-shot Stereo Matching using Large-scale Mixed Images Sources in the Real World—0
ElectricSight: 3D Hazard Monitoring for Power Lines Using Low-Cost Sensors—0
Camera-Only Bird's Eye View Perception: A Neural Approach to LiDAR-Free Environmental Mapping for Autonomous Vehicles—0
LiftFeat: 3D Geometry-Aware Local Feature MatchingCode3
VGLD: Visually-Guided Linguistic Disambiguation for Monocular Depth Scale RecoveryCode0
LMDepth: Lightweight Mamba-based Monocular Depth Estimation for Real-World Deployment—0
Dense Geometry Supervision for Underwater Depth Estimation—0
Occlusion-Aware Self-Supervised Monocular Depth Estimation for Weak-Texture Endoscopic Images—0
VistaDepth: Frequency Modulation With Bias Reweighting For Enhanced Long-Range Depth Estimation—0
Occlusion-Ordered Semantic Instance Segmentation—0
An Online Adaptation Method for Robust Depth Estimation and Visual Odometry in the Open WorldCode0
Cut-and-Splat: Leveraging Gaussian Splatting for Synthetic Data GenerationCode0
DEPTHOR: Depth Enhancement from a Practical Light-Weight dToF Sensor and RGB ImageCode1
Boosting Omnidirectional Stereo Matching with a Pre-trained Depth Foundation ModelCode1
One Look is Enough: A Novel Seamless Patchwise Refinement for Zero-Shot Monocular Depth Estimation Models on High-Resolution Images—0
Intrinsic Image Decomposition for Robust Self-supervised Monocular Depth Estimation on Reflective Surfaces—0
FUSE: Label-Free Image-Event Joint Monocular Depth Estimation via Frequency-Decoupled Alignment and Degradation-Robust FusionCode0
Semi-SD: Semi-Supervised Metric Depth Estimation via Surrounding Cameras for Autonomous DrivingCode0
Radar-Guided Polynomial Fitting for Metric Depth Estimation—0
QuartDepth: Post-Training Quantization for Real-Time Depth Estimation on the EdgeCode1
UniK3D: Universal Camera Monocular 3D EstimationCode4
Jasmine: Harnessing Diffusion Prior for Self-supervised Depth Estimation—0
Multi-view Reconstruction via SfM-guided Monocular Depth Estimation—0
3D Densification for Multi-Map Monocular VSLAM in Endoscopy—0
Endo-FASt3r: Endoscopic Foundation model Adaptation for Structure from motion—0
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