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
Learn to Adapt for Monocular Depth Estimation—0
Unsupervised Simultaneous Learning for Camera Re-Localization and Depth Estimation from Video—0
CroMo: Cross-Modal Learning for Monocular Depth Estimation—0
DiffPoseNet: Direct Differentiable Camera Pose Estimation—0
Semi-Supervised Learning with Mutual Distillation for Monocular Depth Estimation—0
Distortion-Tolerant Monocular Depth Estimation On Omnidirectional Images Using Dual-cubemap—0
Depth-aware Neural Style Transfer using Instance Normalization—0
From 2D to 3D: Re-thinking Benchmarking of Monocular Depth Prediction—0
Unsupervised Learning Based Focal Stack Camera Depth Estimation—0
SelfTune: Metrically Scaled Monocular Depth Estimation through Self-Supervised Learning—0
A high-precision self-supervised monocular visual odometry in foggy weather based on robust cycled generative adversarial networks and multi-task learning aided depth estimation—0
Point Spread Function Estimation of DefocusCode0
3D endoscopic depth estimation using 3D surface-aware constraints—0
PatchMVSNet: Patch-wise Unsupervised Multi-View Stereo for Weakly-Textured Surface Reconstruction—0
Real-Time Hybrid Mapping of Populated Indoor Scenes using a Low-Cost Monocular UAV—0
Time-to-Label: Temporal Consistency for Self-Supervised Monocular 3D Object Detection—0
Fast Neural Architecture Search for Lightweight Dense Prediction Networks—0
Detecting Adversarial Perturbations in Multi-Task PerceptionCode0
Instance-aware multi-object self-supervision for monocular depth prediction—0
Deep Depth from Focal Stack with Defocus Model for Camera-Setting Invariance—0
How Much Depth Information can Radar Contribute to a Depth Estimation Model?—0
On Monocular Depth Estimation and Uncertainty Quantification using Classification Approaches for Regression—0
N-QGN: Navigation Map from a Monocular Camera using Quadtree Generating Networks—0
Light Robust Monocular Depth Estimation For Outdoor Environment Via Monochrome And Color Camera Fusion—0
Synthesizing Photorealistic Images with Deep Generative Learning—0
Joint Learning of Frequency and Spatial Domains for Dense Predictions—0
HeadPosr: End-to-end Trainable Head Pose Estimation using Transformer Encoders—0
StandardSim: A Synthetic Dataset For Retail Environments—0
Scaling up Multi-domain Semantic Segmentation with Sentence Embeddings—0
Maximum Likelihood Uncertainty Estimation: Robustness to OutliersCode0
Towards 3D Scene Reconstruction from Locally Scale-Aligned Monocular Video Depth—0
PanoDepth: A Two-Stage Approach for Monocular Omnidirectional Depth Estimation—0
Light field Rectification based on relative pose estimation—0
Unsupervised Single-shot Depth Estimation using Perceptual ReconstructionCode0
Comparison of Depth Estimation Setups from Stereo Endoscopy and Optical Tracking for Point Measurements—0
GeoFill: Reference-Based Image Inpainting with Better Geometric Understanding—0
Depth Estimation from Single-shot Monocular Endoscope Image Using Image Domain Adaptation And Edge-Aware Depth Estimation—0
MDS-Net: A Multi-scale Depth Stratification Based Monocular 3D Object Detection Algorithm—0
Multi-Robot Collaborative Perception with Graph Neural Networks—0
Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB ImagesCode0
Single-Stage Is Enough: Multi-Person Absolute 3D Pose Estimation—0
Exploiting Pseudo Labels in a Self-Supervised Learning Framework for Improved Monocular Depth Estimation—0
KeyTr: Keypoint Transporter for 3D Reconstruction of Deformable Objects in Videos—0
Neural Window Fully-Connected CRFs for Monocular Depth Estimation—0
Generalizing Interactive Backpropagating Refinement for Dense Prediction Networks—0
Depth estimation of endoscopy using sim-to-real transfer—0
Improving Depth Estimation using Location Information—0
High-Accuracy RGB-D Face Recognition via Segmentation-Aware Face Depth Estimation and Mask-Guided Attention Network—0
NVS-MonoDepth: Improving Monocular Depth Prediction with Novel View Synthesis—0
On the Uncertain Single-View Depths in Colonoscopies—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