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 1276–1300 of 2454 papers

TitleStatusHype
ODDR: Outlier Detection & Dimension Reduction Based Defense Against Adversarial Patches—0
Depth Insight -- Contribution of Different Features to Indoor Single-image Depth Estimation—0
Why Autonomous Vehicles Are Not Ready Yet: A Multi-Disciplinary Review of Problems, Attempted Solutions, and Future Directions—0
Learning based Deep Disentangling Light Field Reconstruction and Disparity Estimation Application—0
DeepMetricEye: Metric Depth Estimation in Periocular VR Imagery—0
PolyMaX: General Dense Prediction with Mask Transformer—0
Learning Robust Multi-Scale Representation for Neural Radiance Fields from Unposed Images—0
Leveraging a realistic synthetic database to learn Shape-from-Shading for estimating the colon depth in colonoscopy images—0
Analysis of NaN Divergence in Training Monocular Depth Estimation Model—0
Continual Learning of Unsupervised Monocular Depth from VideosCode0
Learning to Adapt CLIP for Few-Shot Monocular Depth Estimation—0
Joint Depth Prediction and Semantic Segmentation with Multi-View SAM—0
Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes—0
Deep Imbalanced Regression via Hierarchical Classification Adjustment—0
Learning depth from monocular video sequences—0
Towards Explainability in Monocular Depth Estimation—0
A Quantitative Evaluation of Dense 3D Reconstruction of Sinus Anatomy from Monocular Endoscopic Video—0
Guidance system for Visually Impaired Persons using Deep Learning and Optical flow—0
CLIP meets Model Zoo Experts: Pseudo-Supervision for Visual Enhancement—0
DPF-Nutrition: Food Nutrition Estimation via Depth Prediction and Fusion—0
Towards Abdominal 3-D Scene Rendering from Laparoscopy Surgical Videos using NeRFs—0
FocDepthFormer: Transformer with latent LSTM for Depth Estimation from Focal Stack—0
PU-Ray: Domain-Independent Point Cloud Upsampling via Ray Marching on Neural Implicit SurfaceCode0
Multi-Task Learning-Enabled Automatic Vessel Draft Reading for Intelligent Maritime Surveillance—0
JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling—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