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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 51–100 of 876 papers

TitleStatusHype
UniDepthV2: Universal Monocular Metric Depth Estimation Made SimplerCode5
Distill Any Depth: Distillation Creates a Stronger Monocular Depth EstimatorCode4
Self-supervised Monocular Depth Estimation Robust to Reflective Surface Leveraged by Triplet Mining—0
Monocular Depth Estimation and Segmentation for Transparent Object with Iterative Semantic and Geometric FusionCode1
OrchardDepth: Precise Metric Depth Estimation of Orchard Scene from Monocular Camera Images—0
CDGS: Confidence-Aware Depth Regularization for 3D Gaussian SplattingCode1
SHADeS: Self-supervised Monocular Depth Estimation Through Non-Lambertian Image DecompositionCode0
Pre-training Auto-regressive Robotic Models with 4D Representations—0
Deep Neural Networks for Accurate Depth Estimation with Latent Space Features—0
CoL3D: Collaborative Learning of Single-view Depth and Camera Intrinsics for Metric 3D Shape Recovery—0
MetaFE-DE: Learning Meta Feature Embedding for Depth Estimation from Monocular Endoscopic Images—0
Leveraging Stable Diffusion for Monocular Depth Estimation via Image Semantic Encoding—0
PromptMono: Cross Prompting Attention for Self-Supervised Monocular Depth Estimation in Challenging Environments—0
Enhancing Monocular Depth Estimation with Multi-Source Auxiliary TasksCode0
Survey on Monocular Metric Depth Estimation—0
Video Depth Anything: Consistent Depth Estimation for Super-Long VideosCode5
RDG-GS: Relative Depth Guidance with Gaussian Splatting for Real-time Sparse-View 3D Rendering—0
HSPFormer: Hierarchical Spatial Perception Transformer for Semantic SegmentationCode1
MonSter: Marry Monodepth to Stereo Unleashes PowerCode4
StereoGen: High-quality Stereo Image Generation from a Single Image—0
A Critical Synthesis of Uncertainty Quantification and Foundation Models in Monocular Depth Estimation—0
RePoseD: Efficient Relative Pose Estimation With Known Depth InformationCode1
Relative Pose Estimation through Affine Corrections of Monocular Depth PriorsCode3
DepthMaster: Taming Diffusion Models for Monocular Depth EstimationCode2
Vision-Language Embodiment for Monocular Depth Estimation—0
Distilling Monocular Foundation Model for Fine-grained Depth Completion—0
GeoDepth: From Point-to-Depth to Plane-to-Depth Modeling for Self-Supervised Monocular Depth Estimation—0
Improved Monocular Depth Prediction Using Distance Transform Over Pre-semantic Contours with Self-supervised Neural Networks—0
MetricDepth: Enhancing Monocular Depth Estimation with Deep Metric Learning—0
Learning Monocular Depth from Events via Egomotion Compensation—0
Revisiting Monocular 3D Object Detection from Scene-Level Depth Retargeting to Instance-Level Spatial Refinement—0
Marigold-DC: Zero-Shot Monocular Depth Completion with Guided Diffusion—0
Foundation Models Meet Low-Cost Sensors: Test-Time Adaptation for Rescaling Disparity for Zero-Shot Metric Depth Estimation—0
V-MIND: Building Versatile Monocular Indoor 3D Detector with Diverse 2D Annotations—0
Balancing Shared and Task-Specific Representations: A Hybrid Approach to Depth-Aware Video Panoptic Segmentation—0
GVDepth: Zero-Shot Monocular Depth Estimation for Ground Vehicles based on Probabilistic Cue Fusion—0
LAA-Net: A Physical-prior-knowledge Based Network for Robust Nighttime Depth Estimation—0
Align3R: Aligned Monocular Depth Estimation for Dynamic Videos—0
STATIC : Surface Temporal Affine for TIme Consistency in Video Monocular Depth Estimation—0
FiffDepth: Feed-forward Transformation of Diffusion-Based Generators for Detailed Depth Estimation—0
MonoPP: Metric-Scaled Self-Supervised Monocular Depth Estimation by Planar-Parallax Geometry in Automotive Applications—0
Spatially Visual Perception for End-to-End Robotic Learning—0
PriorDiffusion: Leverage Language Prior in Diffusion Models for Monocular Depth Estimation—0
OceanLens: An Adaptive Backscatter and Edge Correction using Deep Learning Model for Enhanced Underwater ImagingCode1
MGNiceNet: Unified Monocular Geometric Scene UnderstandingCode0
Scalable Autoregressive Monocular Depth Estimation—0
MetricGold: Leveraging Text-To-Image Latent Diffusion Models for Metric Depth EstimationCode0
Mono2Stereo: Monocular Knowledge Transfer for Enhanced Stereo Matching—0
OSMLoc: Single Image-Based Visual Localization in OpenStreetMap with Fused Geometric and Semantic GuidanceCode2
D^3epth: Self-Supervised Depth Estimation with Dynamic Mask in Dynamic ScenesCode0
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