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 951–1000 of 2454 papers

TitleStatusHype
Monocular Depth Decomposition of Semi-Transparent Volume RenderingsCode0
Monocular 3D Object Detection with Pseudo-LiDAR Point CloudCode0
CNN-SVO: Improving the Mapping in Semi-Direct Visual Odometry Using Single-Image Depth PredictionCode0
CNN-SLAM: Real-time dense monocular SLAM with learned depth predictionCode0
A Practical Calibration Method for RGB Micro-Grid Polarimetric CamerasCode0
MGNiceNet: Unified Monocular Geometric Scene UnderstandingCode0
Digging Into Self-Supervised Monocular Depth EstimationCode0
A Physical Model-Guided Framework for Underwater Image Enhancement and Depth EstimationCode0
MetricGold: Leveraging Text-To-Image Latent Diffusion Models for Metric Depth EstimationCode0
ClearGrasp: 3D Shape Estimation of Transparent Objects for ManipulationCode0
METER: a mobile vision transformer architecture for monocular depth estimationCode0
Mapped ConvolutionsCode0
Adaptive LiDAR Sampling and Depth Completion using Ensemble VarianceCode0
Long-Tailed 3D Detection via Multi-Modal FusionCode0
DFR: Depth from Rotation by Uncalibrated Image Rectification with Latitudinal Motion AssumptionCode0
DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task ConsistencyCode0
Challenges of Multi-Modal Coreset Selection for Depth PredictionCode0
Anytime Stereo Image Depth Estimation on Mobile DevicesCode0
3D-SiamMask: Vision-Based Multi-Rotor Aerial-Vehicle Tracking for a Moving ObjectCode0
Lightweight Monocular Depth Estimation Model by Joint End-to-End Filter pruningCode0
L-MAGIC: Language Model Assisted Generation of Images with CoherenceCode0
Maximum Likelihood Uncertainty Estimation: Robustness to OutliersCode0
Detecting Adversarial Perturbations in Multi-Task PerceptionCode0
Leveraging 6DoF Pose Foundation Models For Mapping Marine Sediment BurialCode0
Detail-aware multi-view stereo network for depth estimationCode0
Light Field Compression by Residual CNN Assisted JPEGCode0
DERD-Net: Learning Depth from Event-based Ray DensitiesCode0
Learning Unsupervised Multi-View Stereopsis via Robust Photometric ConsistencyCode0
Learn Stereo, Infer Mono: Siamese Networks for Self-Supervised, Monocular, Depth EstimationCode0
Depth self-supervision for single image novel view synthesisCode0
Learning to Navigate in Complex EnvironmentsCode0
Learning to Synthesize a 4D RGBD Light Field from a Single ImageCode0
Light Field Depth Estimation via Stitched Epipolar Plane ImagesCode0
MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object LocalizationCode0
SharpNet: Fast and Accurate Recovery of Occluding Contours in Monocular Depth EstimationCode0
Learning Single Camera Depth Estimation using Dual-PixelsCode0
Depth Prompting for Sensor-Agnostic Depth EstimationCode0
Learning monocular depth estimation with unsupervised trinocular assumptionsCode0
Learning Multi-modal Information for Robust Light Field Depth EstimationCode0
Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular VideosCode0
An Online Adaptation Method for Robust Depth Estimation and Visual Odometry in the Open WorldCode0
Learning monocular depth estimation infusing traditional stereo knowledgeCode0
Learning Non-Volumetric Depth Fusion Using Successive ReprojectionsCode0
Camera-Independent Single Image Depth Estimation from Defocus BlurCode0
Learning Depth with Convolutional Spatial Propagation NetworkCode0
CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View DepthCode0
Unsupervised Learning of 3D Scene Flow from Monocular CameraCode0
Learning Monocular Depth by Distilling Cross-domain Stereo NetworksCode0
Learning Across Tasks and DomainsCode0
LCD: Learned Cross-Domain Descriptors for 2D-3D MatchingCode0
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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