SOTAVerified

Depth Estimation

Depth Estimation is the task of measuring the distance of each pixel relative to the camera. Depth is extracted from either monocular (single) or stereo (multiple views of a scene) images. Traditional methods use multi-view geometry to find the relationship between the images. Newer methods can directly estimate depth by minimizing the regression loss, or by learning to generate a novel view from a sequence. The most popular benchmarks are KITTI and NYUv2. Models are typically evaluated according to a RMS metric.

Source: DIODE: A Dense Indoor and Outdoor DEpth Dataset

Papers

Showing 18511900 of 2454 papers

TitleStatusHype
Multi-Loss Rebalancing Algorithm for Monocular Depth EstimationCode1
Pixel-Pair Occlusion Relationship Map (P2ORM): Formulation, Inference & Application0
CLIFFNet for Monocular Depth Estimation with Hierarchical Embedding Loss0
Single-Image Depth Prediction Makes Feature Matching EasierCode1
HMOR: Hierarchical Multi-Person Ordinal Relations for Monocular Multi-Person 3D Pose Estimation0
Deep Depth Estimation from Visual-Inertial SLAMCode1
Real-Time Uncertainty Estimation in Computer Vision via Uncertainty-Aware Distribution Distillation0
S^3Net: Semantic-Aware Self-supervised Depth Estimation with Monocular Videos and Synthetic Data0
On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures0
Robust Vision Using Retro Reflective Markers for Remote Handling in ITER0
Adaptive LiDAR Sampling and Depth Completion using Ensemble VarianceCode0
Self-Supervised Monocular 3D Face Reconstruction by Occlusion-Aware Multi-view Geometry ConsistencyCode1
Improving Monocular Depth Estimation by Leveraging Structural Awareness and Complementary Datasets0
Mobile3DRecon: Real-time Monocular 3D Reconstruction on a Mobile Phone0
Feature-metric Loss for Self-supervised Learning of Depth and EgomotionCode1
Multi-person 3D Pose Estimation in Crowded Scenes Based on Multi-View GeometryCode1
Non-Local Spatial Propagation Network for Depth CompletionCode1
Object-Aware Centroid Voting for Monocular 3D Object Detection0
People as Scene Probes0
HDNet: Human Depth Estimation for Multi-Person Camera-Space LocalizationCode1
Defocus Blur Detection via Depth DistillationCode1
Partially Supervised Multi-Task Network for Single-View Dietary Assessment0
P2D: a self-supervised method for depth estimation from polarimetry0
P^2Net: Patch-match and Plane-regularization for Unsupervised Indoor Depth EstimationCode1
Monocular Retinal Depth Estimation and Joint Optic Disc and Cup Segmentation using Adversarial Networks0
Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic GuidanceCode1
360^ Depth Estimation from Multiple Fisheye Images with Origami Crown Representation of IcosahedronCode1
UnRectDepthNet: Self-Supervised Monocular Depth Estimation using a Generic Framework for Handling Common Camera Distortion Models0
AI Playground: Unreal Engine-based Data Ablation Tool for Deep LearningCode1
Continual Adaptation for Deep StereoCode1
EPI-based Oriented Relation Networks for Light Field Depth EstimationCode1
Camera Pose Matters: Improving Depth Prediction by Mitigating Pose Distribution BiasCode1
Unsupervised object-centric video generation and decomposition in 3DCode0
Wasserstein Distances for Stereo Disparity EstimationCode1
Self-supervised Depth Estimation to Regularise Semantic Segmentation in Knee Arthroscopy0
Synergistic saliency and depth prediction for RGB-D saliency detection0
Data-Driven Method for Enhanced Corrosion Assessment of Reinforced Concrete Structures0
EndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearnerCode1
Joint Hand-object 3D Reconstruction from a Single Image with Cross-branch Feature Fusion0
MiniNet: An extremely lightweight convolutional neural network for real-time unsupervised monocular depth estimation0
MTStereo 2.0: improved accuracy of stereo depth estimation withMax-treesCode1
An Advert Creation System for 3D Product Placements0
Increased-Range Unsupervised Monocular Depth Estimation0
Regression Prior NetworksCode1
Self-Supervised Joint Learning Framework of Depth Estimation via Implicit Cues0
AcED: Accurate and Edge-consistent Monocular Depth Estimation0
Depth by Poking: Learning to Estimate Depth from Self-Supervised Grasping0
Targeted Adversarial Perturbations for Monocular Depth PredictionCode1
Attentive Feature Reuse for Multi Task Meta learning0
Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OmniDepthRMSE0.62Unverified
2SphereDepthRMSE0.45Unverified
3Jin et al.RMSE0.42Unverified
4BiFuse with fusionRMSE0.41Unverified
5HoHoNet (ResNet-101)RMSE0.38Unverified
6PanoDepthRMSE0.37Unverified
7BiFuse++RMSE0.37Unverified
8UniFuse with fusionRMSE0.37Unverified
9DisConvRMSE0.37Unverified
10SliceNetRMSE0.37Unverified
#ModelMetricClaimedVerifiedStatus
1A2JmAP8.61Unverified
2PAD-NetRMS0.79Unverified
3MS-CRFRMS0.59Unverified
4DORNRMS0.51Unverified
5FreeformRMS0.43Unverified
6Optimized, freeformRMS0.43Unverified
7VNLRMS0.42Unverified
8BTSRMS0.41Unverified
9TransDepth (AGD+ ViT)RMS0.37Unverified
10AdaBinsRMS0.36Unverified
#ModelMetricClaimedVerifiedStatus
1T2NetAbs Rel0.35Unverified
2MIDASAbs Rel0.31Unverified
3Bhattacharjee et al.Abs Rel0.25Unverified
#ModelMetricClaimedVerifiedStatus
1T2NetAbs Rel0.49Unverified
2MIDASAbs Rel0.42Unverified
3Bhattacharjee et al.Abs Rel0.38Unverified
#ModelMetricClaimedVerifiedStatus
1LeReSabsolute relative error0.1Unverified
2DELTASabsolute relative error0.09Unverified
3Distill Any Depthabsolute relative error0.04Unverified
#ModelMetricClaimedVerifiedStatus
1SDC-DepthRMSE6.92Unverified
2SwinMTLRMSE6.35Unverified
#ModelMetricClaimedVerifiedStatus
1AIP-BrownDelta < 1.250.36Unverified
2LeResDelta < 1.250.23Unverified
#ModelMetricClaimedVerifiedStatus
1H-Net (Ours)Absolute relative error (AbsRel)0.09Unverified
2H-Net (Ours) Full EigenAbsolute relative error (AbsRel)0.08Unverified
#ModelMetricClaimedVerifiedStatus
1GLPDepthDelta < 1.250.43Unverified
2SRDINET (Model A)Delta < 1.250.4Unverified
#ModelMetricClaimedVerifiedStatus
1Atlas (finetuned)RMSE0.17Unverified
2Atlas (plain)RMSE0.17Unverified
#ModelMetricClaimedVerifiedStatus
1LFattNetBadPix(0.01)17.23Unverified
#ModelMetricClaimedVerifiedStatus
1LightDepthNumber of parameters (M)42.6Unverified
#ModelMetricClaimedVerifiedStatus
1UniFuseAbs Rel0.11Unverified
#ModelMetricClaimedVerifiedStatus
1X-TC (Cross-Task Consistency)L1 error1.63Unverified