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 1001–1050 of 2454 papers

TitleStatusHype
CAD2RL: Real Single-Image Flight without a Single Real ImageCode0
Learning Unsupervised Multi-View Stereopsis via Robust Photometric ConsistencyCode0
Learn Stereo, Infer Mono: Siamese Networks for Self-Supervised, Monocular, Depth EstimationCode0
DepthFormer: Exploiting Long-Range Correlation and Local Information for Accurate Monocular Depth EstimationCode0
A Neural Network for Detailed Human Depth Estimation from a Single ImageCode0
Learning to Navigate in Complex EnvironmentsCode0
Learning to Synthesize a 4D RGBD Light Field from a Single ImageCode0
Maximum Likelihood Uncertainty Estimation: Robustness to OutliersCode0
Learning Single Camera Depth Estimation using Dual-PixelsCode0
Depth Estimation via Affinity Learned with Convolutional Spatial Propagation NetworkCode0
Learning Multi-modal Information for Robust Light Field Depth EstimationCode0
Learning Non-Volumetric Depth Fusion Using Successive ReprojectionsCode0
Learning Monocular Depth by Distilling Cross-domain Stereo NetworksCode0
Learning monocular depth estimation infusing traditional stereo knowledgeCode0
Learning monocular depth estimation with unsupervised trinocular assumptionsCode0
Learning Depth with Convolutional Spatial Propagation NetworkCode0
Learning Depth from Single Monocular Images Using Deep Convolutional Neural FieldsCode0
Nighttime Stereo Depth Estimation using Joint Translation-Stereo Learning: Light Effects and Uninformative RegionsCode0
Learning Across Tasks and DomainsCode0
Learning to Adapt for StereoCode0
Enhanced Encoder-Decoder Architecture for Accurate Monocular Depth EstimationCode0
Joint Depth Estimation and Mixture of Rain Removal From a Single ImageCode0
iToF-flow-based High Frame Rate Depth ImagingCode0
IMAGINE-E: Image Generation Intelligence Evaluation of State-of-the-art Text-to-Image ModelsCode0
Tackling water table depth modeling via machine learning: From proxy observations to verifiabilityCode0
LCD: Learned Cross-Domain Descriptors for 2D-3D MatchingCode0
Introducing a Class-Aware Metric for Monocular Depth Estimation: An Automotive PerspectiveCode0
Analysis & Computational Complexity Reduction of Monocular and Stereo Depth Estimation TechniquesCode0
Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB ImagesCode0
Icy Moon Surface Simulation and Stereo Depth Estimation for Sampling AutonomyCode0
Index NetworkCode0
IA-MVS: Instance-Focused Adaptive Depth Sampling for Multi-View StereoCode0
Improving Neural Radiance Fields with Depth-aware Optimization for Novel View SynthesisCode0
Improved Point Transformation Methods For Self-Supervised Depth PredictionCode0
Improving Self-Supervised Single View Depth Estimation by Masking OcclusionCode0
Indoor Depth Completion with Boundary Consistency and Self-AttentionCode0
Investigating Neural Architectures by Synthetic Dataset DesignCode0
Into the Fog: Evaluating Robustness of Multiple Object TrackingCode0
Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object RepresentationCode0
Hybridnet for depth estimation and semantic segmentation—0
EndoPerfect: High-Accuracy Monocular Depth Estimation and 3D Reconstruction for Endoscopic Surgery via NeRF-Stereo Fusion—0
Exploring Depth Contribution for Camouflaged Object Detection—0
Hybrid Light Field Imaging for Improved Spatial Resolution and Depth Range—0
Depth Completion via Inductive Fusion of Planar LIDAR and Monocular Camera—0
Boosting Monocular Depth Estimation with Lightweight 3D Point Fusion—0
HUSH: Holistic Panoramic 3D Scene Understanding using Spherical Harmonics—0
HRDFuse: Monocular 360°Depth Estimation by Collaboratively Learning Holistic-with-Regional Depth Distributions—0
Depth Completion using Plane-Residual Representation—0
Analysis and Improvement of Rank-Ordered Mean Algorithm in Single-Photon LiDAR—0
HRDFuse: Monocular 360deg Depth Estimation by Collaboratively Learning Holistic-With-Regional Depth Distributions—0
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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