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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 901–950 of 2454 papers

TitleStatusHype
Multi-View Stereo by Temporal Nonparametric FusionCode0
Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth EstimationCode0
Consistency Regularisation for Unsupervised Domain Adaptation in Monocular Depth EstimationCode0
Consensus-based Optimization for 3D Human Pose Estimation in Camera CoordinatesCode0
Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth EstimationCode0
Multiple Prior Representation Learning for Self-Supervised Monocular Depth Estimation via Hybrid TransformerCode0
Multi-task Learning for Monocular Depth and Defocus Estimations with Real ImagesCode0
Achieving Risk Control in Online Learning SettingsCode0
DPF^*: improved Depth Potential Function for scale-invariant sulcal depth estimationCode0
Sparse Depth Sensing for Resource-Constrained RobotsCode0
Conf-Net: Toward High-Confidence Dense 3D Point-Cloud with Error-Map PredictionCode0
Multi-body Depth and Camera Pose Estimation from Multiple ViewsCode0
MultiDepth: Single-Image Depth Estimation via Multi-Task Regression and ClassificationCode0
A step towards understanding why classification helps regressionCode0
MorphEyes: Variable Baseline Stereo For Quadrotor NavigationCode0
A Simple Framework for 3D Lensless Imaging with Programmable MasksCode0
On the Viability of Monocular Depth Pre-training for Semantic SegmentationCode0
MonoSIM: Simulating Learning Behaviors of Heterogeneous Point Cloud Object Detectors for Monocular 3D Object DetectionCode0
MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object LocalizationCode0
D-Net: A Generalised and Optimised Deep Network for Monocular Depth EstimationCode0
Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion SegmentationCode0
Monocular Depth Parameterizing NetworksCode0
Monocular Depth Estimation using Multi-Scale Continuous CRFs as Sequential Deep NetworksCode0
Color-Guided Flying Pixel Correction in Depth ImagesCode0
Monocular Depth Estimation Using Cues Inspired by Biological Vision SystemsCode0
Monocular Depth Decomposition of Semi-Transparent Volume RenderingsCode0
Monocular Depth Estimation with Hierarchical Fusion of Dilated CNNs and Soft-Weighted-Sum InferenceCode0
Multi-Modal Attention Networks for Enhanced Segmentation and Depth Estimation of Subsurface Defects in Pulse ThermographyCode0
MGNiceNet: Unified Monocular Geometric Scene UnderstandingCode0
Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on RegressionCode0
MetricGold: Leveraging Text-To-Image Latent Diffusion Models for Metric Depth EstimationCode0
CNN-SVO: Improving the Mapping in Semi-Direct Visual Odometry Using Single-Image Depth PredictionCode0
CNN-SLAM: Real-time dense monocular SLAM with learned depth predictionCode0
METER: a mobile vision transformer architecture for monocular depth estimationCode0
A Practical Calibration Method for RGB Micro-Grid Polarimetric CamerasCode0
Maximum Likelihood Uncertainty Estimation: Robustness to OutliersCode0
Digging Into Self-Supervised Monocular Depth EstimationCode0
Long-Tailed 3D Detection via Multi-Modal FusionCode0
Mapped ConvolutionsCode0
A Physical Model-Guided Framework for Underwater Image Enhancement and Depth EstimationCode0
L-MAGIC: Language Model Assisted Generation of Images with CoherenceCode0
ClearGrasp: 3D Shape Estimation of Transparent Objects for ManipulationCode0
Light Field Depth Estimation via Stitched Epipolar Plane ImagesCode0
Lightweight Monocular Depth Estimation Model by Joint End-to-End Filter pruningCode0
Leveraging 6DoF Pose Foundation Models For Mapping Marine Sediment BurialCode0
Adaptive LiDAR Sampling and Depth Completion using Ensemble VarianceCode0
DFR: Depth from Rotation by Uncalibrated Image Rectification with Latitudinal Motion AssumptionCode0
Learn Stereo, Infer Mono: Siamese Networks for Self-Supervised, Monocular, Depth EstimationCode0
Task-Aware Active Learning for Endoscopic Image AnalysisCode0
DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task ConsistencyCode0
Show:102550
← PrevPage 19 of 50Next →
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