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 701–750 of 2454 papers

TitleStatusHype
A Concise but High-performing Network for Image Guided Depth Completion in Autonomous DrivingCode1
Endo-4DGS: Endoscopic Monocular Scene Reconstruction with 4D Gaussian SplattingCode7
Range-Agnostic Multi-View Depth Estimation With Keyframe SelectionCode1
FoVA-Depth: Field-of-View Agnostic Depth Estimation for Cross-Dataset Generalization—0
InverseMatrixVT3D: An Efficient Projection Matrix-Based Approach for 3D Occupancy PredictionCode1
Icy Moon Surface Simulation and Stereo Depth Estimation for Sampling AutonomyCode0
EndoGaussian: Real-time Gaussian Splatting for Dynamic Endoscopic Scene ReconstructionCode0
MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View StereoCode3
Stereo-Matching Knowledge Distilled Monocular Depth Estimation Filtered by Multiple Disparity Consistency—0
Depth Anything: Unleashing the Power of Large-Scale Unlabeled DataCode9
TDC-less Direct Time-of-Flight Imaging Using Spiking Neural Networks—0
Self-supervised Event-based Monocular Depth Estimation using Cross-modal Consistency—0
Surgical-DINO: Adapter Learning of Foundation Models for Depth Estimation in Endoscopic SurgeryCode2
A Study on Self-Supervised Pretraining for Vision Problems in Gastrointestinal EndoscopyCode1
InseRF: Text-Driven Generative Object Insertion in Neural 3D Scenes—0
RadarCam-Depth: Radar-Camera Fusion for Depth Estimation with Learned Metric ScaleCode2
NeRFmentation: NeRF-based Augmentation for Monocular Depth Estimation—0
Hi-Map: Hierarchical Factorized Radiance Field for High-Fidelity Monocular Dense Mapping—0
Denoising Vision TransformersCode3
Depth-discriminative Metric Learning for Monocular 3D Object Detection—0
Flexible Depth Completion for Sparse and Varying Point Densities—0
iToF-flow-based High Frame Rate Depth ImagingCode0
Diffusion Handles Enabling 3D Edits for Diffusion Models by Lifting Activations to 3D—0
Global and Hierarchical Geometry Consistency Priors for Few-shot NeRFs in Indoor ScenesCode1
Coherence As Texture - Passive Textureless 3D Reconstruction by Self-interference—0
Learning Deformable Hypothesis Sampling for Accurate PatchMatch Multi-View StereoCode1
Manydepth2: Motion-Aware Self-Supervised Multi-Frame Monocular Depth Estimation in Dynamic ScenesCode1
Pola4All: survey of polarimetric applications and an open-source toolkit to analyze polarizationCode1
Harnessing Diffusion Models for Visual Perception with Meta PromptsCode1
Lift-Attend-Splat: Bird's-eye-view camera-lidar fusion using transformers—0
DUSt3R: Geometric 3D Vision Made EasyCode5
NeRF-VO: Real-Time Sparse Visual Odometry with Neural Radiance Fields—0
PPEA-Depth: Progressive Parameter-Efficient Adaptation for Self-Supervised Monocular Depth Estimation—0
Zero-Shot Metric Depth with a Field-of-View Conditioned Diffusion Model—0
DDOS: The Drone Depth and Obstacle Segmentation Dataset—0
Atlantis: Enabling Underwater Depth Estimation with Stable DiffusionCode1
Long-Tailed 3D Detection via Multi-Modal FusionCode0
From-Ground-To-Objects: Coarse-to-Fine Self-supervised Monocular Depth Estimation of Dynamic Objects with Ground Contact Prior—0
CT-MVSNet: Efficient Multi-View Stereo with Cross-scale TransformerCode1
OccNeRF: Advancing 3D Occupancy Prediction in LiDAR-Free EnvironmentsCode2
Text2Immersion: Generative Immersive Scene with 3D Gaussians—0
ReCoRe: Regularized Contrastive Representation Learning of World Model—0
EVP: Enhanced Visual Perception using Inverse Multi-Attentive Feature Refinement and Regularized Image-Text AlignmentCode1
Instance-aware Multi-Camera 3D Object Detection with Structural Priors Mining and Self-Boosting Learning—0
Mitigating Perspective Distortion-induced Shape Ambiguity in Image Crops—0
GenDepth: Generalizing Monocular Depth Estimation for Arbitrary Camera Parameters via Ground Plane Embedding—0
Camera-based 3D Semantic Scene Completion with Sparse Guidance NetworkCode1
Fine Dense Alignment of Image Bursts through Camera Pose and Depth Estimation—0
Camera Height Doesn't Change: Unsupervised Training for Metric Monocular Road-Scene Depth Estimation—0
Artificial Neural Network for Estimation of Physical Parameters of Sea Water using LiDAR Waveforms—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