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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 301–350 of 876 papers

TitleStatusHype
Lightweight Monocular Depth Estimation through Guided DecodingCode1
MonoMVSNet: Monocular Priors Guided Multi-View Stereo NetworkCode1
Improving Deep Regression with Ordinal EntropyCode1
P3Depth: Monocular Depth Estimation with a Piecewise Planarity PriorCode1
R-MSFM: Recurrent Multi-Scale Feature Modulation for Monocular Depth EstimatingCode1
Connecting the Dots: Learning Representations for Active Monocular Depth Estimation—0
Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery—0
Language-Based Depth Hints for Monocular Depth Estimation—0
ElectricSight: 3D Hazard Monitoring for Power Lines Using Low-Cost Sensors—0
EgoM2P: Egocentric Multimodal Multitask Pretraining—0
Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation—0
A Survey on Deep Learning Techniques for Stereo-based Depth Estimation—0
KineDepth: Utilizing Robot Kinematics for Online Metric Depth Estimation—0
EdgeConv with Attention Module for Monocular Depth Estimation—0
Composite Learning for Robust and Effective Dense Predictions—0
Adversarial Patch Attacks on Monocular Depth Estimation Networks—0
LAA-Net: A Physical-prior-knowledge Based Network for Robust Nighttime Depth Estimation—0
Large Language Models Can Understanding Depth from Monocular Images—0
Competitive Simplicity for Multi-Task Learning for Real-Time Foggy Scene Understanding via Domain Adaptation—0
Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes—0
CoL3D: Collaborative Learning of Single-view Depth and Camera Intrinsics for Metric 3D Shape Recovery—0
DwinFormer: Dual Window Transformers for End-to-End Monocular Depth Estimation—0
Improving Depth Estimation using Location Information—0
Large-scale Monocular Depth Estimation in the Wild—0
DRL-ISP: Multi-Objective Camera ISP with Deep Reinforcement Learning—0
Double Refinement Network for Efficient Indoor Monocular Depth Estimation—0
Don't Forget The Past: Recurrent Depth Estimation from Monocular Video—0
Domain-Transferred Synthetic Data Generation for Improving Monocular Depth Estimation—0
CLIP Can Understand Depth—0
A Simple Baseline for Supervised Surround-view Depth Estimation—0
Domain Decluttering: Simplifying Images to Mitigate Synthetic-Real Domain Shift and Improve Depth Estimation—0
Domain Adaptive Monocular Depth Estimation With Semantic Information—0
CLIFFNet for Monocular Depth Estimation with Hierarchical Embedding Loss—0
D-NPC: Dynamic Neural Point Clouds for Non-Rigid View Synthesis from Monocular Video—0
Adversarial Attacks on Monocular Depth Estimation—0
AcED: Accurate and Edge-consistent Monocular Depth Estimation—0
Joint Task-Recursive Learning for Semantic Segmentation and Depth Estimation—0
Distortion-Tolerant Monocular Depth Estimation On Omnidirectional Images Using Dual-cubemap—0
CI-Net: Contextual Information for Joint Semantic Segmentation and Depth Estimation—0
Distortion-aware Monocular Depth Estimation for Omnidirectional Images—0
Distilling Monocular Foundation Model for Fine-grained Depth Completion—0
Aperture Supervision for Monocular Depth Estimation—0
Cascade Network for Self-Supervised Monocular Depth Estimation—0
Discrete-Continuous Depth Estimation from a Single Image—0
APARATE: Adaptive Adversarial Patch for CNN-based Monocular Depth Estimation for Autonomous Navigation—0
Disambiguating Monocular Depth Estimation with a Single Transient—0
Can Scale-Consistent Monocular Depth Be Learned in a Self-Supervised Scale-Invariant Manner?—0
CamLessMonoDepth: Monocular Depth Estimation with Unknown Camera Parameters—0
A Novel Monocular Disparity Estimation Network with Domain Transformation and Ambiguity Learning—0
Camera-Only Bird's Eye View Perception: A Neural Approach to LiDAR-Free Environmental Mapping for Autonomous Vehicles—0
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