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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 401–450 of 876 papers

TitleStatusHype
Benchmarking Robustness of Endoscopic Depth Estimation with Synthetically Corrupted DataCode0
DepthART: Monocular Depth Estimation as Autoregressive Refinement Task—0
Depth Estimation Based on 3D Gaussian Splatting Siamese Defocus—0
Towards Single-Lens Controllable Depth-of-Field Imaging via Depth-Aware Point Spread FunctionsCode0
GRIN: Zero-Shot Metric Depth with Pixel-Level Diffusion—0
Advancing Depth Anything Model for Unsupervised Monocular Depth Estimation in Endoscopy—0
EDADepth: Enhanced Data Augmentation for Monocular Depth EstimationCode0
TanDepth: Leveraging Global DEMs for Metric Monocular Depth Estimation in UAVs—0
Introducing a Class-Aware Metric for Monocular Depth Estimation: An Automotive PerspectiveCode0
SG-MIM: Structured Knowledge Guided Efficient Pre-training for Dense Prediction—0
iConFormer: Dynamic Parameter-Efficient Tuning with Input-Conditioned Adaptation—0
Large Language Models Can Understanding Depth from Monocular Images—0
EvLight++: Low-Light Video Enhancement with an Event Camera: A Large-Scale Real-World Dataset, Novel Method, and More—0
Adversarial Manhole: Challenging Monocular Depth Estimation and Semantic Segmentation Models with Patch AttackCode0
NimbleD: Enhancing Self-supervised Monocular Depth Estimation with Pseudo-labels and Large-scale Video Pre-trainingCode0
TranSplat: Generalizable 3D Gaussian Splatting from Sparse Multi-View Images with Transformers—0
Enhanced Scale-aware Depth Estimation for Monocular Endoscopic Scenes with Geometric Modeling—0
Towards Robust Monocular Depth Estimation in Non-Lambertian Surfaces—0
Embodiment: Self-Supervised Depth Estimation Based on Camera Models—0
High-Precision Self-Supervised Monocular Depth Estimation with Rich-Resource Prior—0
BetterDepth: Plug-and-Play Diffusion Refiner for Zero-Shot Monocular Depth Estimation—0
UMono: Physical Model Informed Hybrid CNN-Transformer Framework for Underwater Monocular Depth Estimation—0
Physical Adversarial Attack on Monocular Depth Estimation via Shape-Varying Patches—0
ScaleDepth: Decomposing Metric Depth Estimation into Scale Prediction and Relative Depth EstimationCode0
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
D-NPC: Dynamic Neural Point Clouds for Non-Rigid View Synthesis from Monocular Video—0
Unsupervised Monocular Depth Estimation Based on Hierarchical Feature-Guided Diffusion—0
ToSA: Token Selective Attention for Efficient Vision Transformers—0
Multiple Prior Representation Learning for Self-Supervised Monocular Depth Estimation via Hybrid TransformerCode0
Back to the Color: Learning Depth to Specific Color Transformation for Unsupervised Depth EstimationCode0
MambaDepth: Enhancing Long-range Dependency for Self-Supervised Fine-Structured Monocular Depth Estimation—0
Neural Surface Reconstruction from Sparse Views Using Epipolar Geometry—0
Uncertainty-guided Optimal Transport in Depth Supervised Sparse-View 3D Gaussian—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
DCPI-Depth: Explicitly Infusing Dense Correspondence Prior to Unsupervised Monocular Depth Estimation—0
Consistency Regularisation for Unsupervised Domain Adaptation in Monocular Depth EstimationCode0
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
Promoting CNNs with Cross-Architecture Knowledge Distillation for Efficient Monocular Depth Estimation—0
MonoPCC: Photometric-invariant Cycle Constraint for Monocular Depth Estimation of Endoscopic Images—0
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