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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 551–600 of 2454 papers

TitleStatusHype
Cross-spectral Gated-RGB Stereo Depth Estimation—0
Depth Reconstruction with Neural Signed Distance Fields in Structured Light Systems—0
Depth Prompting for Sensor-Agnostic Depth EstimationCode0
CRF360D: Monocular 360 Depth Estimation via Spherical Fully-Connected CRFs—0
Dusk Till Dawn: Self-supervised Nighttime Stereo Depth Estimation using Visual Foundation ModelsCode1
GEOcc: Geometrically Enhanced 3D Occupancy Network with Implicit-Explicit Depth Fusion and Contextual Self-Supervision—0
FA-Depth: Toward Fast and Accurate Self-supervised Monocular Depth EstimationCode0
Towards Task-Compatible Compressible RepresentationsCode0
KPNDepth: Depth Estimation of Lane Images under Complex Rainy Environment—0
EndoDAC: Efficient Adapting Foundation Model for Self-Supervised Depth Estimation from Any Endoscopic CameraCode2
CLIP with Quality Captions: A Strong Pretraining for Vision Tasks—0
The RoboDrive Challenge: Drive Anytime Anywhere in Any Condition—0
SceneFactory: A Workflow-centric and Unified Framework for Incremental Scene Modeling—0
Ensuring UAV Safety: A Vision-only and Real-time Framework for Collision Avoidance Through Object Detection, Tracking, and Distance Estimation—0
MGS-SLAM: Monocular Sparse Tracking and Gaussian Mapping with Depth Smooth Regularization—0
A Construct-Optimize Approach to Sparse View Synthesis without Camera Pose—0
DreamScene4D: Dynamic Multi-Object Scene Generation from Monocular VideosCode3
M^2Depth: Self-supervised Two-Frame Multi-camera Metric Depth Estimation—0
Domain-Transferred Synthetic Data Generation for Improving Monocular Depth Estimation—0
Depth Priors in Removal Neural Radiance Fields—0
Tackling water table depth modeling via machine learning: From proxy observations to verifiabilityCode0
Invisible Stitch: Generating Smooth 3D Scenes with Depth Inpainting—0
Underwater Variable Zoom: Depth-Guided Perception Network for Underwater Image EnhancementCode1
A Novel Spike Transformer Network for Depth Estimation from Event Cameras via Cross-modality Knowledge Distillation—0
Promoting CNNs with Cross-Architecture Knowledge Distillation for Efficient Monocular Depth Estimation—0
The Third Monocular Depth Estimation Challenge—0
MonoPCC: Photometric-invariant Cycle Constraint for Monocular Depth Estimation of Endoscopic Images—0
Mining Supervision for Dynamic Regions in Self-Supervised Monocular Depth EstimationCode1
SGFormer: Spherical Geometry Transformer for 360 Depth Estimation—0
Self-Supervised Monocular Depth Estimation in the Dark: Towards Data Distribution Compensation—0
GScream: Learning 3D Geometry and Feature Consistent Gaussian Splatting for Object Removal—0
High-fidelity Endoscopic Image Synthesis by Utilizing Depth-guided Neural Surfaces—0
SPIdepth: Strengthened Pose Information for Self-supervised Monocular Depth EstimationCode2
BLINK: Multimodal Large Language Models Can See but Not Perceive—0
How to deal with glare for improved perception of Autonomous Vehicles—0
Digging into contrastive learning for robust depth estimation with diffusion modelsCode1
Virtually Enriched NYU Depth V2 Dataset for Monocular Depth Estimation: Do We Need Artificial Augmentation?Code0
Into the Fog: Evaluating Robustness of Multiple Object TrackingCode0
On the Robustness of Language Guidance for Low-Level Vision Tasks: Findings from Depth EstimationCode0
GLID: Pre-training a Generalist Encoder-Decoder Vision Model—0
Implicit and Explicit Language Guidance for Diffusion-based Visual Perception—0
Boosting Self-Supervision for Single-View Scene Completion via Knowledge Distillation—0
Stereo-LiDAR Depth Estimation with Deformable Propagation and Learned Disparity-Depth ConversionCode1
Depth Estimation using Weighted-loss and Transfer Learning—0
Self-supervised Monocular Depth Estimation on Water Scenes via Specular Reflection Prior—0
MonoSelfRecon: Purely Self-Supervised Explicit Generalizable 3D Reconstruction of Indoor Scenes from Monocular RGB Views—0
RoadBEV: Road Surface Reconstruction in Bird's Eye ViewCode3
Incremental Joint Learning of Depth, Pose and Implicit Scene Representation on Monocular Camera in Large-scale Scenes—0
Enhanced Radar Perception via Multi-Task Learning: Towards Refined Data for Sensor Fusion Applications—0
HawkDrive: A Transformer-driven Visual Perception System for Autonomous Driving in Night SceneCode0
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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