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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 251–275 of 876 papers

TitleStatusHype
Stereo-Matching Knowledge Distilled Monocular Depth Estimation Filtered by Multiple Disparity Consistency—0
Depth Anything: Unleashing the Power of Large-Scale Unlabeled DataCode9
Self-supervised Event-based Monocular Depth Estimation using Cross-modal Consistency—0
A Study on Self-Supervised Pretraining for Vision Problems in Gastrointestinal EndoscopyCode1
InseRF: Text-Driven Generative Object Insertion in Neural 3D Scenes—0
NeRFmentation: NeRF-based Augmentation for Monocular Depth Estimation—0
Global and Hierarchical Geometry Consistency Priors for Few-shot NeRFs in Indoor ScenesCode1
Manydepth2: Motion-Aware Self-Supervised Multi-Frame Monocular Depth Estimation in Dynamic ScenesCode1
Harnessing Diffusion Models for Visual Perception with Meta PromptsCode1
Lift-Attend-Splat: Bird's-eye-view camera-lidar fusion using transformers—0
Zero-Shot Metric Depth with a Field-of-View Conditioned Diffusion Model—0
PPEA-Depth: Progressive Parameter-Efficient Adaptation for Self-Supervised Monocular Depth Estimation—0
Atlantis: Enabling Underwater Depth Estimation with Stable DiffusionCode1
From-Ground-To-Objects: Coarse-to-Fine Self-supervised Monocular Depth Estimation of Dynamic Objects with Ground Contact Prior—0
EVP: Enhanced Visual Perception using Inverse Multi-Attentive Feature Refinement and Regularized Image-Text AlignmentCode1
GenDepth: Generalizing Monocular Depth Estimation for Arbitrary Camera Parameters via Ground Plane Embedding—0
Camera Height Doesn't Change: Unsupervised Training for Metric Monocular Road-Scene Depth Estimation—0
Repurposing Diffusion-Based Image Generators for Monocular Depth EstimationCode4
Deeper into Self-Supervised Monocular Indoor Depth EstimationCode1
Enhancing Diffusion Models with 3D Perspective Geometry Constraints—0
Depth-Regularized Optimization for 3D Gaussian Splatting in Few-Shot ImagesCode2
Camera-Independent Single Image Depth Estimation from Defocus BlurCode0
SelfOcc: Self-Supervised Vision-Based 3D Occupancy PredictionCode2
Depth Insight -- Contribution of Different Features to Indoor Single-image Depth Estimation—0
MonoDiffusion: Self-Supervised Monocular Depth Estimation Using Diffusion ModelCode1
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