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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
MonoPCC: Photometric-invariant Cycle Constraint for Monocular Depth Estimation of Endoscopic Images—0
Mining Supervision for Dynamic Regions in Self-Supervised Monocular Depth EstimationCode1
Self-Supervised Monocular Depth Estimation in the Dark: Towards Data Distribution Compensation—0
GScream: Learning 3D Geometry and Feature Consistent Gaussian Splatting for Object Removal—0
High-fidelity Endoscopic Image Synthesis by Utilizing Depth-guided Neural Surfaces—0
SPIdepth: Strengthened Pose Information for Self-supervised Monocular Depth EstimationCode2
Virtually Enriched NYU Depth V2 Dataset for Monocular Depth Estimation: Do We Need Artificial Augmentation?Code0
Into the Fog: Evaluating Robustness of Multiple Object TrackingCode0
On the Robustness of Language Guidance for Low-Level Vision Tasks: Findings from Depth EstimationCode0
Self-supervised Monocular Depth Estimation on Water Scenes via Specular Reflection Prior—0
RoadBEV: Road Surface Reconstruction in Bird's Eye ViewCode3
WorDepth: Variational Language Prior for Monocular Depth EstimationCode1
Adaptive Discrete Disparity Volume for Self-supervised Monocular Depth Estimation—0
BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression TasksCode1
VSRD: Instance-Aware Volumetric Silhouette Rendering for Weakly Supervised 3D Object DetectionCode1
FlowDepth: Decoupling Optical Flow for Self-Supervised Monocular Depth Estimation—0
UniDepth: Universal Monocular Metric Depth EstimationCode5
ECoDepth: Effective Conditioning of Diffusion Models for Monocular Depth EstimationCode3
F^2Depth: Self-supervised Indoor Monocular Depth Estimation via Optical Flow Consistency and Feature Map Synthesis—0
Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous DrivingCode2
Track Everything Everywhere Fast and Robustly—0
Leveraging Near-Field Lighting for Monocular Depth Estimation from Endoscopy Videos—0
Language-Based Depth Hints for Monocular Depth Estimation—0
DepthFM: Fast Monocular Depth Estimation with Flow MatchingCode4
FutureDepth: Learning to Predict the Future Improves Video Depth Estimation—0
SSAP: A Shape-Sensitive Adversarial Patch for Comprehensive Disruption of Monocular Depth Estimation in Autonomous Navigation Applications—0
SwinMTL: A Shared Architecture for Simultaneous Depth Estimation and Semantic Segmentation from Monocular Camera ImagesCode1
Touch-GS: Visual-Tactile Supervised 3D Gaussian Splatting—0
METER: a mobile vision transformer architecture for monocular depth estimationCode0
WaveShot: A Compact Portable Unmanned Surface Vessel for Dynamic Water Surface Videography and Media Production—0
Adaptive Fusion of Single-View and Multi-View Depth for Autonomous DrivingCode2
D4D: An RGBD diffusion model to boost monocular depth estimationCode0
What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?Code3
Stealing Stable Diffusion Prior for Robust Monocular Depth EstimationCode1
Scalable Vision-Based 3D Object Detection and Monocular Depth Estimation for Autonomous DrivingCode1
DD-VNB: A Depth-based Dual-Loop Framework for Real-time Visually Navigated Bronchoscopy—0
Pyramid Feature Attention Network for Monocular Depth Prediction—0
Kick Back & Relax++: Scaling Beyond Ground-Truth Depth with SlowTV & CribsTVCode2
PCDepth: Pattern-based Complementary Learning for Monocular Depth Estimation by Best of Both Worlds—0
TIE-KD: Teacher-Independent and Explainable Knowledge Distillation for Monocular Depth EstimationCode0
Zero-BEV: Zero-shot Projection of Any First-Person Modality to BEV Maps—0
An Endoscopic Chisel: Intraoperative Imaging Carves 3D Anatomical Models—0
Unveiling the Depths: A Multi-Modal Fusion Framework for Challenging Scenarios—0
MAL: Motion-Aware Loss with Temporal and Distillation Hints for Self-Supervised Depth Estimation—0
Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation—0
MoD-SLAM: Monocular Dense Mapping for Unbounded 3D Scene Reconstruction—0
CLIP Can Understand Depth—0
Diffusion-based Light Field Synthesis—0
Depth Anything in Medical Images: A Comparative Study—0
Endo-4DGS: Endoscopic Monocular Scene Reconstruction with 4D Gaussian SplattingCode7
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