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 1651–1700 of 2454 papers

TitleStatusHype
Joint Self-supervised Depth and Optical Flow Estimation towards Dynamic Objects—0
Joint Semantic Segmentation and Depth Estimation with Deep Convolutional Networks—0
Joint Spatial and Angular Super-Resolution from a Single Image—0
Joint Task-Recursive Learning for Semantic Segmentation and Depth Estimation—0
Joint Voxel and Coordinate Regression for Accurate 3D Facial Landmark Localization—0
Just-in-Time Reconstruction: Inpainting Sparse Maps using Single View Depth Predictors as Priors—0
KeyTr: Keypoint Transporter for 3D Reconstruction of Deformable Objects in Videos—0
KineDepth: Utilizing Robot Kinematics for Online Metric Depth Estimation—0
KPNDepth: Depth Estimation of Lane Images under Complex Rainy Environment—0
LAA-Net: A Physical-prior-knowledge Based Network for Robust Nighttime Depth Estimation—0
LAFFNet: A Lightweight Adaptive Feature Fusion Network for Underwater Image Enhancement—0
Language-Based Depth Hints for Monocular Depth Estimation—0
Laparoscopic Scene Analysis for Intraoperative Visualisation of Gamma Probe Signals in Minimally Invasive Cancer Surgery—0
Large Language Models Can Understanding Depth from Monocular Images—0
Large-scale Monocular Depth Estimation in the Wild—0
Layered Depth Refinement with Mask Guidance—0
LEAD: LiDAR Extender for Autonomous Driving—0
Learned Binocular-Encoding Optics for RGBD Imaging Using Joint Stereo and Focus Cues—0
Learning 3D Photography Videos via Self-supervised Diffusion on Single Images—0
Learning a Domain-Agnostic Visual Representation for Autonomous Driving via Contrastive Loss—0
Learning based Deep Disentangling Light Field Reconstruction and Disparity Estimation Application—0
Learning Common Representation from RGB and Depth Images—0
Learning Deeply Supervised Good Features to Match for Dense Monocular Reconstruction—0
Learning depth from monocular video sequences—0
Learning Depth from Monocular Videos Using Synthetic Data: A Temporally-Consistent Domain Adaptation Approach—0
Learning Depth from Single Images with Deep Neural Network Embedding Focal Length—0
Learning Depth With Very Sparse Supervision—0
Learning Depth via Leveraging Semantics: Self-supervised Monocular Depth Estimation with Both Implicit and Explicit Semantic Guidance—0
Learning Feature Decomposition for Domain Adaptive Monocular Depth Estimation—0
Learning Good Features to Transfer Across Tasks and Domains—0
Learning Inverse Laplacian Pyramid for Progressive Depth Completion—0
Learning Monocular Depth Estimation via Selective Distillation of Stereo Knowledge—0
Learning Monocular Depth from Events via Egomotion Compensation—0
Learning Monocular Depth in Dynamic Environment via Context-aware Temporal Attention—0
Learning Optical Flow, Depth, and Scene Flow without Real-World Labels—0
Learning Ordinal Relationships for Mid-Level Vision—0
Learning Phase Mask for Privacy-Preserving Passive Depth Estimation—0
Learning Robust Multi-Scale Representation for Neural Radiance Fields from Unposed Images—0
Learning Scene Structure Guidance via Cross-Task Knowledge Transfer for Single Depth Super-Resolution—0
Learning Semantic Segmentation from Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach—0
Learning Single-Image Depth from Videos using Quality Assessment Networks—0
Learning Structured Gaussians to Approximate Deep Ensembles—0
SafeAug: Safety-Critical Driving Data Augmentation from Naturalistic Datasets—0
SAID-NeRF: Segmentation-AIDed NeRF for Depth Completion of Transparent Objects—0
SAMSNeRF: Segment Anything Model (SAM) Guides Dynamic Surgical Scene Reconstruction by Neural Radiance Field (NeRF)—0
SANPO: A Scene Understanding, Accessibility and Human Navigation Dataset—0
SCADE: NeRFs from Space Carving with Ambiguity-Aware Depth Estimates—0
Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions—0
Scalable Autoregressive Monocular Depth Estimation—0
Scalable Uncertainty for Computer Vision with Functional Variational Inference—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