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 276–300 of 2454 papers

TitleStatusHype
TACO: Learning Multi-modal Action Models with Synthetic Chains-of-Thought-and-ActionCode2
PanoDreamer: Optimization-Based Single Image to 360 3D Scene With DiffusionCode2
SimC3D: A Simple Contrastive 3D Pretraining Framework Using RGB ImagesCode0
MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic VideosCode5
DualPM: Dual Posed-Canonical Point Maps for 3D Shape and Pose Reconstruction—0
MT3DNet: Multi-Task learning Network for 3D Surgical Scene Reconstruction—0
LAA-Net: A Physical-prior-knowledge Based Network for Robust Nighttime Depth Estimation—0
MultiGO: Towards Multi-level Geometry Learning for Monocular 3D Textured Human Reconstruction—0
Align3R: Aligned Monocular Depth Estimation for Dynamic Videos—0
Dense Scene Reconstruction from Light-Field Images Affected by Rolling ShutterCode0
Perception Tokens Enhance Visual Reasoning in Multimodal Language Models—0
GSGTrack: Gaussian Splatting-Guided Object Pose Tracking from RGB Videos—0
Amodal Depth Anything: Amodal Depth Estimation in the Wild—0
Dual Exposure Stereo for Extended Dynamic Range 3D Imaging—0
Single-Shot Metric Depth from Focused Plenoptic Cameras—0
HoloDrive: Holistic 2D-3D Multi-Modal Street Scene Generation for Autonomous Driving—0
AVS-Net: Audio-Visual Scale Net for Self-supervised Monocular Metric Depth Estimation—0
STATIC : Surface Temporal Affine for TIme Consistency in Video Monocular Depth Estimation—0
Mutli-View 3D Reconstruction using Knowledge DistillationCode0
FiffDepth: Feed-forward Transformation of Diffusion-Based Generators for Detailed Depth Estimation—0
SpaRC: Sparse Radar-Camera Fusion for 3D Object DetectionCode0
Gaussian Splashing: Direct Volumetric Rendering Underwater—0
MonoPP: Metric-Scaled Self-Supervised Monocular Depth Estimation by Planar-Parallax Geometry in Automotive Applications—0
Video Depth without Video Models—0
360Recon: An Accurate Reconstruction Method Based on Depth Fusion from 360 Images—0
Show:102550
← PrevPage 12 of 99Next →
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