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 51–100 of 2454 papers

TitleStatusHype
RadarRGBD A Multi-Sensor Fusion Dataset for Perception with RGB-D and mmWave RadarCode0
Multi-Label Stereo Matching for Transparent Scene Depth EstimationCode1
M3Depth: Wavelet-Enhanced Depth Estimation on Mars via Mutual Boosting of Dual-Modal Data—0
DB3D-L: Depth-aware BEV Feature Transformation for Accurate 3D Lane Detection—0
IA-MVS: Instance-Focused Adaptive Depth Sampling for Multi-View StereoCode0
3D Visual Illusion Depth EstimationCode1
Always Clear Depth: Robust Monocular Depth Estimation under Adverse WeatherCode1
MonoMobility: Zero-Shot 3D Mobility Analysis from Monocular Videos—0
SurgPose: Generalisable Surgical Instrument Pose Estimation using Zero-Shot Learning and Stereo Vision—0
Attention on the SphereCode4
Depth Anything with Any Prior—0
JointDistill: Adaptive Multi-Task Distillation for Joint Depth Estimation and Scene Segmentation—0
Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image AnalysisCode7
Boosting Zero-shot Stereo Matching using Large-scale Mixed Images Sources in the Real World—0
Reinforcement Learning-Based Monocular Vision Approach for Autonomous UAV Landing—0
Edge-Enabled VIO with Long-Tracked Features for High-Accuracy Low-Altitude IoT NavigationCode1
ElectricSight: 3D Hazard Monitoring for Power Lines Using Low-Cost Sensors—0
Camera-Only Bird's Eye View Perception: A Neural Approach to LiDAR-Free Environmental Mapping for Autonomous Vehicles—0
MonoCoP: Chain-of-Prediction for Monocular 3D Object Detection—0
Self-Supervised Learning for Robotic Leaf Manipulation: A Hybrid Geometric-Neural Approach—0
LiftFeat: 3D Geometry-Aware Local Feature MatchingCode3
VGLD: Visually-Guided Linguistic Disambiguation for Monocular Depth Scale RecoveryCode0
DELTA: Dense Depth from Events and LiDAR using Transformer's Attention—0
In-situ and Non-contact Etch Depth Prediction in Plasma Etching via Machine Learning (ANN & BNN) and Digital Image Colorimetry—0
PosePilot: Steering Camera Pose for Generative World Models with Self-supervised Depth—0
LMDepth: Lightweight Mamba-based Monocular Depth Estimation for Real-World Deployment—0
JointDiT: Enhancing RGB-Depth Joint Modeling with Diffusion Transformers—0
HoloTime: Taming Video Diffusion Models for Panoramic 4D Scene GenerationCode2
Dense Geometry Supervision for Underwater Depth Estimation—0
Occlusion-Aware Self-Supervised Monocular Depth Estimation for Weak-Texture Endoscopic Images—0
UniVG: A Generalist Diffusion Model for Unified Image Generation and Editing—0
DERD-Net: Learning Depth from Event-based Ray DensitiesCode0
VistaDepth: Frequency Modulation With Bias Reweighting For Enhanced Long-Range Depth Estimation—0
Seurat: From Moving Points to DepthCode2
Occlusion-Ordered Semantic Instance Segmentation—0
Enhancing Pothole Detection and Characterization: Integrated Segmentation and Depth Estimation in Road Anomaly Systems—0
TSGS: Improving Gaussian Splatting for Transparent Surface Reconstruction via Normal and De-lighting Priors—0
Perception Encoder: The best visual embeddings are not at the output of the networkCode8
Privacy-Preserving Operating Room Workflow Analysis using Digital Twins—0
Metric-Solver: Sliding Anchored Metric Depth Estimation from a Single Image—0
TacoDepth: Towards Efficient Radar-Camera Depth Estimation with One-stage Fusion—0
An Online Adaptation Method for Robust Depth Estimation and Visual Odometry in the Open WorldCode0
Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual PerceptionCode1
DeepWheel: Generating a 3D Synthetic Wheel Dataset for Design and Performance Evaluation—0
Cut-and-Splat: Leveraging Gaussian Splatting for Synthetic Data GenerationCode0
Geo4D: Leveraging Video Generators for Geometric 4D Scene ReconstructionCode3
FlashDepth: Real-time Streaming Video Depth Estimation at 2K ResolutionCode3
POMATO: Marrying Pointmap Matching with Temporal Motion for Dynamic 3D ReconstructionCode2
Stereo-LiDAR Fusion by Semi-Global Matching With Discrete Disparity-Matching Cost and SemidensificationCode0
Endo3R: Unified Online Reconstruction from Dynamic Monocular Endoscopic Video—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