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 1176–1200 of 2454 papers

TitleStatusHype
Frequency-Aware Self-Supervised Monocular Depth EstimationCode1
Map-free Visual Relocalization: Metric Pose Relative to a Single ImageCode2
Detaching and Boosting: Dual Engine for Scale-Invariant Self-Supervised Monocular Depth EstimationCode1
TRADE: Object Tracking with 3D Trajectory and Ground Depth Estimates for UAVs—0
Self-Supervised Monocular Depth Underwater—0
MOTSLAM: MOT-assisted monocular dynamic SLAM using single-view depth estimation—0
Depth Is All You Need for Monocular 3D Detection—0
Multi-Camera Collaborative Depth Prediction via Consistent Structure Estimation—0
Image Masking for Robust Self-Supervised Monocular Depth EstimationCode1
Non-learning Stereo-aided Depth Completion under Mis-projection via Selective Stereo Matching—0
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier ConvolutionsCode1
PlaneDepth: Self-supervised Depth Estimation via Orthogonal PlanesCode1
Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuningCode1
Self-Supervised Monocular Depth Estimation: Solving the Edge-Fattening ProblemCode1
Lightweight Monocular Depth Estimation with an Edge Guided Network—0
Contrastive Unsupervised Learning of World Model with Invariant Causal Features—0
Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions—0
DELTAR: Depth Estimation from a Light-weight ToF Sensor and RGB Image—0
CrossDTR: Cross-view and Depth-guided Transformers for 3D Object DetectionCode1
WaterNeRF: Neural Radiance Fields for Underwater Scenes—0
Towards Multimodal Multitask Scene Understanding Models for Indoor Mobile Agents—0
SAPA: Similarity-Aware Point Affiliation for Feature UpsamplingCode1
UDepth: Fast Monocular Depth Estimation for Visually-guided Underwater RobotsCode1
DeepFusion: A Robust and Modular 3D Object Detector for Lidars, Cameras and Radars—0
Image-to-Image Translation for Autonomous Driving from Coarsely-Aligned Image Pairs—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