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 601–650 of 2454 papers

TitleStatusHype
Deep Phase Coded Image Prior—0
Know Your Neighbors: Improving Single-View Reconstruction via Spatial Vision-Language ReasoningCode2
MVD-Fusion: Single-view 3D via Depth-consistent Multi-view Generation—0
MonoCD: Monocular 3D Object Detection with Complementary DepthsCode2
WorDepth: Variational Language Prior for Monocular Depth EstimationCode1
Adaptive Discrete Disparity Volume for Self-supervised Monocular Depth Estimation—0
CHOSEN: Contrastive Hypothesis Selection for Multi-View Depth Refinement—0
Improving Bird's Eye View Semantic Segmentation by Task Decomposition—0
Flare-Free Vision: Empowering Uformer with Depth InsightsCode1
BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression TasksCode1
MaGRITTe: Manipulative and Generative 3D Realization from Image, Topview and Text—0
VSRD: Instance-Aware Volumetric Silhouette Rendering for Weakly Supervised 3D Object DetectionCode1
NeSLAM: Neural Implicit Mapping and Self-Supervised Feature Tracking With Depth Completion and DenoisingCode0
SAID-NeRF: Segmentation-AIDed NeRF for Depth Completion of Transparent Objects—0
FlowDepth: Decoupling Optical Flow for Self-Supervised Monocular Depth Estimation—0
UniDepth: Universal Monocular Metric Depth EstimationCode5
ECoDepth: Effective Conditioning of Diffusion Models for Monocular Depth EstimationCode3
ModaLink: Unifying Modalities for Efficient Image-to-PointCloud Place RecognitionCode1
F^2Depth: Self-supervised Indoor Monocular Depth Estimation via Optical Flow Consistency and Feature Map Synthesis—0
DN-Splatter: Depth and Normal Priors for Gaussian Splatting and MeshingCode4
Track Everything Everywhere Fast and Robustly—0
Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous DrivingCode2
Leveraging Near-Field Lighting for Monocular Depth Estimation from Endoscopy Videos—0
Elite360D: Towards Efficient 360 Depth Estimation via Semantic- and Distance-Aware Bi-Projection Fusion—0
Spike-NeRF: Neural Radiance Field Based On Spike Camera—0
Configurable Holography: Towards Display and Scene Adaptation—0
Depth Estimation fusing Image and Radar Measurements with Uncertain Directions—0
Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal EstimationCode7
Language-Based Depth Hints for Monocular Depth Estimation—0
Learning to Project for Cross-Task Knowledge Distillation—0
DepthFM: Fast Monocular Depth Estimation with Flow MatchingCode4
When Do We Not Need Larger Vision Models?Code9
Geometric Constraints in Deep Learning Frameworks: A Survey—0
FutureDepth: Learning to Predict the Future Improves Video Depth Estimation—0
GraphBEV: Towards Robust BEV Feature Alignment for Multi-Modal 3D Object Detection—0
SSAP: A Shape-Sensitive Adversarial Patch for Comprehensive Disruption of Monocular Depth Estimation in Autonomous Navigation Applications—0
MSI-NeRF: Linking Omni-Depth with View Synthesis through Multi-Sphere Image aided Generalizable Neural Radiance FieldCode1
SwinMTL: A Shared Architecture for Simultaneous Depth Estimation and Semantic Segmentation from Monocular Camera ImagesCode1
Robust Shape Fitting for 3D Scene AbstractionCode2
Region-aware Distribution Contrast: A Novel Approach to Multi-Task Partially Supervised Learning—0
FeatUp: A Model-Agnostic Framework for Features at Any ResolutionCode5
Touch-GS: Visual-Tactile Supervised 3D Gaussian Splatting—0
Improving Distant 3D Object Detection Using 2D Box Supervision—0
SM4Depth: Seamless Monocular Metric Depth Estimation across Multiple Cameras and Scenes by One ModelCode1
METER: a mobile vision transformer architecture for monocular depth estimationCode0
WaveShot: A Compact Portable Unmanned Surface Vessel for Dynamic Water Surface Videography and Media Production—0
Q-SLAM: Quadric Representations for Monocular SLAM—0
D4D: An RGBD diffusion model to boost monocular depth estimationCode0
SGE: Structured Light System Based on Gray Code with an Event Camera—0
Adaptive Fusion of Single-View and Multi-View Depth for Autonomous DrivingCode2
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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