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

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Showing 201–250 of 2454 papers

TitleStatusHype
Densely Constrained Depth Estimator for Monocular 3D Object DetectionCode1
EVP: Enhanced Visual Perception using Inverse Multi-Attentive Feature Refinement and Regularized Image-Text AlignmentCode1
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary CellsCode1
A geometry-aware deep network for depth estimation in monocular endoscopyCode1
BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression TasksCode1
Deep Multi-view Depth Estimation with Predicted UncertaintyCode1
ACDNet: Adaptively Combined Dilated Convolution for Monocular Panorama Depth EstimationCode1
BaseBoostDepth: Exploiting Larger Baselines For Self-supervised Monocular Depth EstimationCode1
BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural NetworksCode1
Deep Two-View Structure-from-Motion RevisitedCode1
DEFLOW: Self-supervised 3D Motion Estimation of Debris FlowCode1
Bayes' Rays: Uncertainty Quantification for Neural Radiance FieldsCode1
Deep Multi-View Stereo gone wildCode1
A Hybrid Sparse-Dense Monocular SLAM System for Autonomous DrivingCode1
A General and Adaptive Robust Loss FunctionCode1
AI Playground: Unreal Engine-based Data Ablation Tool for Deep LearningCode1
EPI-based Oriented Relation Networks for Light Field Depth EstimationCode1
Excavating the Potential Capacity of Self-Supervised Monocular Depth EstimationCode1
ES-Net: An Efficient Stereo Matching NetworkCode1
Deeper Depth Prediction with Fully Convolutional Residual NetworksCode1
BEV-LGKD: A Unified LiDAR-Guided Knowledge Distillation Framework for BEV 3D Object DetectionCode1
BEVNeXt: Reviving Dense BEV Frameworks for 3D Object DetectionCode1
Deep Depth From FocusCode1
Deeper into Self-Supervised Monocular Indoor Depth EstimationCode1
Deep Depth Estimation from Visual-Inertial SLAMCode1
Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual PerceptionCode1
Deep Depth Estimation from Thermal Image: Dataset, Benchmark, and ChallengesCode1
ENRICH: Multi-purposE dataset for beNchmaRking In Computer vision and pHotogrammetryCode1
Estimating Image Depth in the Comics DomainCode1
Bi3D: Stereo Depth Estimation via Binary ClassificationsCode1
Bidirectional Attention Network for Monocular Depth EstimationCode1
BiFuse: Monocular 360 Depth Estimation via Bi-Projection FusionCode1
BiFuse++: Self-supervised and Efficient Bi-projection Fusion for 360 Depth EstimationCode1
Depth-Aware Endoscopic Video InpaintingCode1
Deep Color Mismatch Correction In Stereoscopic 3D ImagesCode1
EndoMUST: Monocular Depth Estimation for Robotic Endoscopy via End-to-end Multi-step Self-supervised TrainingCode1
EndoOmni: Zero-Shot Cross-Dataset Depth Estimation in Endoscopy by Robust Self-Learning from Noisy LabelsCode1
Depth-aware Volume Attention for Texture-less Stereo MatchingCode1
A Concise but High-performing Network for Image Guided Depth Completion in Autonomous DrivingCode1
Depth estimation from 4D light field videosCode1
Depth Estimation from Monocular Images and Sparse Radar DataCode1
Depth Estimation from Monocular Images and Sparse radar using Deep Ordinal Regression NetworkCode1
EndoDepth: A Benchmark for Assessing Robustness in Endoscopic Depth PredictionCode1
A Confidence-based Iterative Solver of Depths and Surface Normals for Deep Multi-view StereoCode1
End-to-End Pseudo-LiDAR for Image-Based 3D Object DetectionCode1
AeDet: Azimuth-invariant Multi-view 3D Object DetectionCode1
Deep Ordinal Regression Network for Monocular Depth EstimationCode1
DCDepth: Progressive Monocular Depth Estimation in Discrete Cosine DomainCode1
Deconstructing Self-Supervised Monocular Reconstruction: The Design Decisions that MatterCode1
Energy-Efficient Adaptive 3D SensingCode1
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All datasetsStanford2D3D PanoramicNYU-Depth V2DCMeBDthequeScanNetV2Cityscapes testDIODEKITTI 2015Mars DTM EstimationScanNet4D Light Field DatasetKITTI Eigen split

Benchmark Results

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