SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–225 of 876 papers

TitleStatusHype
Disentangling Object Motion and Occlusion for Unsupervised Multi-frame Monocular DepthCode1
LocalBins: Improving Depth Estimation by Learning Local DistributionsCode1
Learning Occlusion-Aware Coarse-to-Fine Depth Map for Self-supervised Monocular Depth EstimationCode1
Monocular Depth Distribution Alignment with Low ComputationCode1
Lightweight Monocular Depth Estimation through Guided DecodingCode1
OmniFusion: 360 Monocular Depth Estimation via Geometry-Aware FusionCode1
Automated Distance Estimation for Wildlife Camera TrappingCode1
Transformers in Self-Supervised Monocular Depth Estimation with Unknown Camera IntrinsicsCode1
Global-Local Path Networks for Monocular Depth Estimation with Vertical CutDepthCode1
Chitransformer: Towards Reliable Stereo From CuesCode1
Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth EstimationCode1
GCNDepth: Self-supervised Monocular Depth Estimation based on Graph Convolutional NetworkCode1
Toward Practical Monocular Indoor Depth EstimationCode1
A benchmark with decomposed distribution shifts for 360 monocular depth estimationCode1
360MonoDepth: High-Resolution 360° Monocular Depth EstimationCode1
SUB-Depth: Self-distillation and Uncertainty Boosting Self-supervised Monocular Depth EstimationCode1
Absolute distance prediction based on deep learning object detection and monocular depth estimation modelsCode1
Self-Supervised Monocular Depth Estimation with Internal Feature FusionCode1
Excavating the Potential Capacity of Self-Supervised Monocular Depth EstimationCode1
Improving 360 Monocular Depth Estimation via Non-local Dense Prediction Transformer and Joint Supervised and Self-supervised LearningCode1
Advancing Self-supervised Monocular Depth Learning with Sparse LiDARCode1
RVMDE: Radar Validated Monocular Depth Estimation for RoboticsCode1
Improving Semi-Supervised and Domain-Adaptive Semantic Segmentation with Self-Supervised Depth EstimationCode1
Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth EstimationCode1
StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimationCode1
Show:102550
← PrevPage 9 of 36Next →

No leaderboard results yet.