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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
Towards Robust Monocular Depth Estimation in Non-Lambertian Surfaces—0
Depth Any Canopy: Leveraging Depth Foundation Models for Canopy Height EstimationCode1
BodySLAM: A Generalized Monocular Visual SLAM Framework for Surgical ApplicationsCode1
Embodiment: Self-Supervised Depth Estimation Based on Camera Models—0
High-Precision Self-Supervised Monocular Depth Estimation with Rich-Resource Prior—0
BaseBoostDepth: Exploiting Larger Baselines For Self-supervised Monocular Depth EstimationCode1
HybridDepth: Robust Metric Depth Fusion by Leveraging Depth from Focus and Single-Image PriorsCode2
UMono: Physical Model Informed Hybrid CNN-Transformer Framework for Underwater Monocular Depth Estimation—0
BetterDepth: Plug-and-Play Diffusion Refiner for Zero-Shot Monocular Depth Estimation—0
Physical Adversarial Attack on Monocular Depth Estimation via Shape-Varying Patches—0
Diffusion Models for Monocular Depth Estimation: Overcoming Challenging ConditionsCode2
Mono-ViFI: A Unified Learning Framework for Self-supervised Single- and Multi-frame Monocular Depth EstimationCode2
IDOL: Unified Dual-Modal Latent Diffusion for Human-Centric Joint Video-Depth GenerationCode2
ProDepth: Boosting Self-Supervised Multi-Frame Monocular Depth with Probabilistic FusionCode1
ScaleDepth: Decomposing Metric Depth Estimation into Scale Prediction and Relative Depth EstimationCode0
SCIPaD: Incorporating Spatial Clues into Unsupervised Pose-Depth Joint LearningCode1
Uni-DVPS: Unified Model for Depth-Aware Video Panoptic SegmentationCode1
Deep Learning-based Depth Estimation Methods from Monocular Image and Videos: A Comprehensive Survey—0
Dense Monocular Motion Segmentation Using Optical Flow and Pseudo Depth Map: A Zero-Shot Approach—0
WaterMono: Teacher-Guided Anomaly Masking and Enhancement Boosting for Robust Underwater Self-Supervised Monocular Depth EstimationCode0
Depth Anywhere: Enhancing 360 Monocular Depth Estimation via Perspective Distillation and Unlabeled Data Augmentation—0
GenMM: Geometrically and Temporally Consistent Multimodal Data Generation for Video and LiDAR—0
DurLAR: A High-fidelity 128-channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery for Multi-modal Autonomous Driving ApplicationsCode2
Unsupervised Monocular Depth Estimation Based on Hierarchical Feature-Guided Diffusion—0
D-NPC: Dynamic Neural Point Clouds for Non-Rigid View Synthesis from Monocular Video—0
ToSA: Token Selective Attention for Efficient Vision Transformers—0
Multiple Prior Representation Learning for Self-Supervised Monocular Depth Estimation via Hybrid TransformerCode0
Scale-Invariant Monocular Depth Estimation via SSI DepthCode1
Depth Anything V2Code9
Back to the Color: Learning Depth to Specific Color Transformation for Unsupervised Depth EstimationCode0
Self-supervised Adversarial Training of Monocular Depth Estimation against Physical-World AttacksCode1
Neural Surface Reconstruction from Sparse Views Using Epipolar Geometry—0
MambaDepth: Enhancing Long-range Dependency for Self-Supervised Fine-Structured Monocular Depth Estimation—0
Flash3D: Feed-Forward Generalisable 3D Scene Reconstruction from a Single ImageCode3
Self-Supervised Geometry-Guided Initialization for Robust Monocular Visual OdometryCode4
Uncertainty-guided Optimal Transport in Depth Supervised Sparse-View 3D Gaussian—0
Consistency Regularisation for Unsupervised Domain Adaptation in Monocular Depth EstimationCode0
GenWarp: Single Image to Novel Views with Semantic-Preserving Generative WarpingCode3
DCPI-Depth: Explicitly Infusing Dense Correspondence Prior to Unsupervised Monocular Depth Estimation—0
A Comparative Study on Multi-task Uncertainty Quantification in Semantic Segmentation and Monocular Depth Estimation—0
Estimating Depth of Monocular Panoramic Image with Teacher-Student Model Fusing Equirectangular and Spherical Representations—0
Enhanced Object Tracking by Self-Supervised Auxiliary Depth Estimation Learning—0
Depth Prompting for Sensor-Agnostic Depth EstimationCode0
FA-Depth: Toward Fast and Accurate Self-supervised Monocular Depth EstimationCode0
A Construct-Optimize Approach to Sparse View Synthesis without Camera Pose—0
Domain-Transferred Synthetic Data Generation for Improving Monocular Depth Estimation—0
Depth Priors in Removal Neural Radiance Fields—0
Invisible Stitch: Generating Smooth 3D Scenes with Depth Inpainting—0
MonoPCC: Photometric-invariant Cycle Constraint for Monocular Depth Estimation of Endoscopic Images—0
The Third Monocular Depth Estimation Challenge—0
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