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 1051–1100 of 2454 papers

TitleStatusHype
Multi-Task Self-Supervised Learning for Image Segmentation Task—0
A Disparity Refinement Framework for Learning-based Stereo Matching Methods in Cross-domain Setting for Laparoscopic Images—0
SceneScape: Text-Driven Consistent Scene Generation—0
STEPS: Joint Self-supervised Nighttime Image Enhancement and Depth EstimationCode1
Uncertainty-Driven Dense Two-View Structure from Motion—0
Recurrent Structure Attention Guidance for Depth Super-Resolution—0
Adversarial Training of Self-supervised Monocular Depth Estimation against Physical-World AttacksCode1
Structure Flow-Guided Network for Real Depth Super-Resolution—0
AudioEar: Single-View Ear Reconstruction for Personalized Spatial AudioCode1
HDPV-SLAM: Hybrid Depth-augmented Panoramic Visual SLAM for Mobile Mapping System with Tilted LiDAR and Panoramic Visual Camera—0
Leveraging the Third Dimension in Contrastive Learning—0
Learning Good Features to Transfer Across Tasks and Domains—0
On the Adversarial Robustness of Camera-based 3D Object DetectionCode1
Improving Deep Regression with Ordinal EntropyCode1
FG-Depth: Flow-Guided Unsupervised Monocular Depth Estimation—0
Unsupervised Light Field Depth Estimation via Multi-view Feature Matching with Occlusion Prediction—0
Booster: a Benchmark for Depth from Images of Specular and Transparent Surfaces—0
SoftEnNet: Symbiotic Monocular Depth Estimation and Lumen Segmentation for Colonoscopy Endorobots—0
Self-Supervised Learning from Images with a Joint-Embedding Predictive ArchitectureCode2
Behind the Scenes: Density Fields for Single View ReconstructionCode2
SwinDepth: Unsupervised Depth Estimation using Monocular Sequences via Swin Transformer and Densely Cascaded NetworkCode1
Dyna-DepthFormer: Multi-frame Transformer for Self-Supervised Depth Estimation in Dynamic Scenes—0
S^2Net: Accurate Panorama Depth Estimation on Spherical Surface—0
Deep Planar Parallax for Monocular Depth Estimation—0
A Study on the Generality of Neural Network Structures for Monocular Depth EstimationCode1
All in Tokens: Unifying Output Space of Visual Tasks via Soft TokenCode1
DepthP+P: Metric Accurate Monocular Depth Estimation using Planar and Parallax—0
BS3D: Building-scale 3D Reconstruction from RGB-D Images—0
Multi-Task Learning with Knowledge Distillation for Dense Prediction—0
Achievement-Based Training Progress Balancing for Multi-Task LearningCode0
3D Distillation: Improving Self-Supervised Monocular Depth Estimation on Reflective Surfaces—0
CORE: Co-planarity Regularized Monocular Geometry Estimation with Weak Supervision—0
Consistent Depth Prediction for Transparent Object Reconstruction from RGB-D Camera—0
SlaBins: Fisheye Depth Estimation using Slanted Bins on Road Environments—0
DPS-Net: Deep Polarimetric Stereo Depth Estimation—0
CL-MVSNet: Unsupervised Multi-View Stereo with Dual-Level Contrastive LearningCode1
Self-supervised Monocular Underwater Depth Recovery, Image Restoration, and a Real-sea Video DatasetCode1
Guiding Local Feature Matching with Surface Curvature—0
Semantic Information in Contrastive LearningCode0
ObjectFusion: Multi-modal 3D Object Detection with Object-Centric Fusion—0
Multi-body Depth and Camera Pose Estimation from Multiple ViewsCode0
Semi-Supervised Stereo-Based 3D Object Detection via Cross-View Consensus—0
GeoMVSNet: Learning Multi-View Stereo With Geometry PerceptionCode2
Spatio-Focal Bidirectional Disparity Estimation From a Dual-Pixel Image—0
LightedDepth: Video Depth Estimation in Light of Limited Inference View AnglesCode1
Depth Estimation From Indoor Panoramas With Neural Scene RepresentationCode1
HRDFuse: Monocular 360deg Depth Estimation by Collaboratively Learning Holistic-With-Regional Depth Distributions—0
Omnimatte3D: Associating Objects and Their Effects in Unconstrained Monocular Video—0
Deep Depth Estimation From Thermal ImageCode0
OmniVidar: Omnidirectional Depth Estimation From Multi-Fisheye ImagesCode1
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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