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
H-Net: Unsupervised Attention-based Stereo Depth Estimation Leveraging Epipolar Geometry—0
FourierNets enable the design of highly non-local optical encoders for computational imagingCode1
MonoGRNet: A General Framework for Monocular 3D Object Detection—0
Depth Completion using Plane-Residual Representation—0
Discrete Cosine Transform Network for Guided Depth Map Super-ResolutionCode1
Revisiting Light Field Rendering with Deep Anti-Aliasing Neural NetworkCode1
Dynamic Fusion Network For Light Field Depth Estimation—0
Single Image Depth Estimation: An Overview—0
Learning Multi-modal Information for Robust Light Field Depth EstimationCode0
VR3Dense: Voxel Representation Learning for 3D Object Detection and Monocular Dense Depth ReconstructionCode1
Domain Adaptive Monocular Depth Estimation With Semantic Information—0
Exploring Geometric Consistency for Monocular 3D Object Detection—0
Improving Online Performance Prediction for Semantic Segmentation—0
iELAS: An ELAS-Based Energy-Efficient Accelerator for Real-Time Stereo Matching on FPGA Platform—0
Stereo Matching by Self-supervision of Multiscopic Vision—0
SVDistNet: Self-Supervised Near-Field Distance Estimation on Surround View Fisheye Cameras—0
Learning optical flow from still imagesCode1
Deep Monocular 3D Human Pose Estimation via Cascaded Dimension-Lifting—0
Self-supervised Learning of Depth Inference for Multi-view StereoCode1
Multi-View Multi-Person 3D Pose Estimation with Plane Sweep StereoCode1
Objects are Different: Flexible Monocular 3D Object DetectionCode1
Instantaneous Stereo Depth Estimation of Real-World Stimuli with a Neuromorphic Stereo-Vision Setup—0
S2R-DepthNet: Learning a Generalizable Depth-specific Structural RepresentationCode1
Improved and efficient inter-vehicle distance estimation using road gradients of both ego and target vehicles—0
Deep Two-View Structure-from-Motion RevisitedCode1
A Front-End for Dense Monocular SLAM using a Learned Outlier Mask Prior—0
RGB-D Local Implicit Function for Depth Completion of Transparent ObjectsCode1
Unsupervised Learning of Monocular Depth and Ego-Motion Using Multiple MasksCode1
LED2-Net: Monocular 360 Layout Estimation via Differentiable Depth RenderingCode1
Unpaired Single-Image Depth Synthesis with cycle-consistent Wasserstein GANs—0
DynOcc: Learning Single-View Depth from Dynamic Occlusion Cues—0
Sparse Auxiliary Networks for Unified Monocular Depth Prediction and CompletionCode2
Geometric Unsupervised Domain Adaptation for Semantic Segmentation—0
Does it work outside this benchmark? Introducing the Rigid Depth Constructor tool, depth validation dataset construction in rigid scenes for the massesCode1
Bayesian Deep Basis Fitting for Depth Completion with Uncertainty—0
Generalizing to the Open World: Deep Visual Odometry with Online Adaptation—0
Adaptive Surface Normal Constraint for Depth EstimationCode1
MINE: Towards Continuous Depth MPI with NeRF for Novel View SynthesisCode1
Vision Transformers for Dense PredictionCode3
A Framework for 3D Tracking of Frontal Dynamic Objects in Autonomous Cars—0
SaccadeCam: Adaptive Visual Attention for Monocular Depth SensingCode0
Volumetric Propagation Network: Stereo-LiDAR Fusion for Long-Range Depth Estimation—0
Learning Scene Structure Guidance via Cross-Task Knowledge Transfer for Single Depth Super-Resolution—0
M3DSSD: Monocular 3D Single Stage Object DetectorCode1
Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Types—0
Stereo Object Matching Network—0
Revisiting Self-Supervised Monocular Depth EstimationCode0
Monocular Depth Estimation through Virtual-world Supervision and Real-world SfM Self-SupervisionCode1
Transformer-Based Attention Networks for Continuous Pixel-Wise PredictionCode1
Unsupervised Learning of Depth Estimation and Visual Odometry for Sparse Light Field Cameras—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