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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 351–400 of 876 papers

TitleStatusHype
High-Resolution Synthetic RGB-D Datasets for Monocular Depth Estimation—0
AutoColor: Learned Light Power Control for Multi-Color HologramsCode0
TaskPrompter: Spatial-Channel Multi-Task Prompting for Dense Scene UnderstandingCode2
Depth-Relative Self Attention for Monocular Depth Estimation—0
A geometry-aware deep network for depth estimation in monocular endoscopyCode1
Pose Constraints for Consistent Self-supervised Monocular Depth and Ego-motionCode0
360^ High-Resolution Depth Estimation via Uncertainty-aware Structural Knowledge Transfer—0
DINOv2: Learning Robust Visual Features without SupervisionCode6
Self-Supervised Learning based Depth Estimation from Monocular ImagesCode0
The Second Monocular Depth Estimation Challenge—0
iDisc: Internal Discretization for Monocular Depth EstimationCode3
Joint 2D-3D Multi-Task Learning on Cityscapes-3D: 3D Detection, Segmentation, and Depth EstimationCode2
altiro3D: Scene representation from single image and novel view synthesisCode1
ENRICH: Multi-purposE dataset for beNchmaRking In Computer vision and pHotogrammetryCode1
SemHint-MD: Learning from Noisy Semantic Labels for Self-Supervised Monocular Depth Estimation—0
TiDy-PSFs: Computational Imaging with Time-Averaged Dynamic Point-Spread-Functions—0
DDP: Diffusion Model for Dense Visual PredictionCode2
An intelligent modular real-time vision-based system for environment perceptionCode1
Multi-Frame Self-Supervised Depth Estimation with Multi-Scale Feature Fusion in Dynamic Scenes—0
SCADE: NeRFs from Space Carving with Ambiguity-Aware Depth Estimates—0
Monocular Visual-Inertial Depth EstimationCode1
Boosting Weakly Supervised Object Detection using Fusion and Priors from Hallucinated Depth—0
CoDEPS: Online Continual Learning for Depth Estimation and Panoptic SegmentationCode1
A Simple Framework for 3D Occupancy Estimation in Autonomous DrivingCode2
A Simple Baseline for Supervised Surround-view Depth Estimation—0
DiffusionDepth: Diffusion Denoising Approach for Monocular Depth EstimationCode2
Lifelong-MonoDepth: Lifelong Learning for Multi-Domain Monocular Metric Depth EstimationCode1
RM-Depth: Unsupervised Learning of Recurrent Monocular Depth in Dynamic ScenesCode1
DwinFormer: Dual Window Transformers for End-to-End Monocular Depth Estimation—0
Unleashing Text-to-Image Diffusion Models for Visual PerceptionCode2
APARATE: Adaptive Adversarial Patch for CNN-based Monocular Depth Estimation for Autonomous Navigation—0
Monocular Depth Estimation using Diffusion Models—0
ZoeDepth: Zero-shot Transfer by Combining Relative and Metric DepthCode5
Depth Estimation and Image Restoration by Deep Learning from Defocused Images—0
Bokeh Rendering Based on Adaptive Depth Calibration Network—0
Learning 3D Photography Videos via Self-supervised Diffusion on Single Images—0
On the Metrics for Evaluating Monocular Depth Estimation—0
GlocalFuse-Depth: Fusing Transformers and CNNs for All-day Self-supervised Monocular Depth Estimation—0
Self-Supervised Monocular Depth Estimation with Self-Reference Distillation and Disparity Offset RefinementCode0
Long Range Object-Level Monocular Depth Estimation for UAVs—0
URCDC-Depth: Uncertainty Rectified Cross-Distillation with CutFlip for Monocular Depth EstimationCode1
VA-DepthNet: A Variational Approach to Single Image Depth PredictionCode1
EVEN: An Event-Based Framework for Monocular Depth Estimation at Adverse Night Conditions—0
Adversarial Training of Self-supervised Monocular Depth Estimation against Physical-World AttacksCode1
Learning Good Features to Transfer Across Tasks and Domains—0
Improving Deep Regression with Ordinal EntropyCode1
FG-Depth: Flow-Guided Unsupervised Monocular Depth Estimation—0
SoftEnNet: Symbiotic Monocular Depth Estimation and Lumen Segmentation for Colonoscopy Endorobots—0
Booster: a Benchmark for Depth from Images of Specular and Transparent Surfaces—0
SwinDepth: Unsupervised Depth Estimation using Monocular Sequences via Swin Transformer and Densely Cascaded NetworkCode1
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