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 1901–1925 of 2454 papers

TitleStatusHype
Toward Better SSIM Loss for Unsupervised Monocular Depth Estimation—0
Toward Depth Estimation Using Mask-Based Lensless Cameras—0
Toward Real-world BEV Perception: Depth Uncertainty Estimation via Gaussian Splatting—0
Towards Abdominal 3-D Scene Rendering from Laparoscopy Surgical Videos using NeRFs—0
Towards an AI-based Early Warning System for Bridge Scour—0
Towards Augmented Reality-based Suturing in Monocular Laparoscopic Training—0
Monocular Outdoor Semantic Mapping with a Multi-task Network—0
Towards Comprehensive Representation Enhancement in Semantics-guided Self-supervised Monocular Depth Estimation—0
Towards Depth Foundation Model: Recent Trends in Vision-Based Depth Estimation—0
Towards Domain Generalization for Multi-view 3D Object Detection in Bird-Eye-View—0
Towards Explainability in Monocular Depth Estimation—0
Towards Full-parameter and Parameter-efficient Self-learning For Endoscopic Camera Depth Estimation—0
Towards Full-to-Empty Room Generation with Structure-Aware Feature Encoding and Soft Semantic Region-Adaptive Normalization—0
Towards General Purpose Geometry-Preserving Single-View Depth Estimation—0
Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models—0
Towards Keypoint Guided Self-Supervised Depth Estimation—0
Towards Multimodal Depth Estimation from Light Fields—0
Towards Multimodal Multitask Scene Understanding Models for Indoor Mobile Agents—0
Towards Panoptic 3D Parsing for Single Image in the Wild—0
Towards Robust Monocular Depth Estimation in Non-Lambertian Surfaces—0
Towards Scale-Aware Full Surround Monodepth with Transformers—0
Towards Scene Understanding: Unsupervised Monocular Depth Estimation With Semantic-Aware Representation—0
Towards Unified Depth and Semantic Prediction From a Single Image—0
Towards urban scenes understanding through polarization cues—0
Track Everything Everywhere Fast and Robustly—0
Show:102550
← PrevPage 77 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