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 1251–1300 of 2454 papers

TitleStatusHype
Survey on Semantic Stereo Matching / Semantic Depth Estimation—0
SVDistNet: Self-Supervised Near-Field Distance Estimation on Surround View Fisheye Cameras—0
SVDM: Single-View Diffusion Model for Pseudo-Stereo 3D Object Detection—0
Symmetry-aware Depth Estimation using Deep Neural Networks—0
SynDeMo: Synergistic Deep Feature Alignment for Joint Learning of Depth and Ego-Motion—0
SynDistNet: Self-Supervised Monocular Fisheye Camera Distance Estimation Synergized with Semantic Segmentation for Autonomous Driving—0
Synergistic saliency and depth prediction for RGB-D saliency detection—0
Syn-Mediverse: A Multimodal Synthetic Dataset for Intelligent Scene Understanding of Healthcare Facilities—0
Synthesizing a 4D Spatio-Angular Consistent Light Field from a Single Image—0
Synthesizing Photorealistic Images with Deep Generative Learning—0
Synthetic Lunar Terrain: A Multimodal Open Dataset for Training and Evaluating Neuromorphic Vision Algorithms—0
TacoDepth: Towards Efficient Radar-Camera Depth Estimation with One-stage Fusion—0
TanDepth: Leveraging Global DEMs for Metric Monocular Depth Estimation in UAVs—0
Task-Driven Deep Image Enhancement Network for Autonomous Driving in Bad Weather—0
Taskology: Utilizing Task Relations at Scale—0
TDC-less Direct Time-of-Flight Imaging Using Spiking Neural Networks—0
Tech Report: Divide and Conquer 3D Real-Time Reconstruction for Improved IGS—0
Temporally Consistent Depth Prediction with Flow-Guided Memory Units—0
Temporally Consistent Online Depth Estimation in Dynamic Scenes—0
TexAVi: Generating Stereoscopic VR Video Clips from Text Descriptions—0
Text2Immersion: Generative Immersive Scene with 3D Gaussians—0
The Aleatoric Uncertainty Estimation Using a Separate Formulation with Virtual Residuals—0
The BabyView dataset: High-resolution egocentric videos of infants' and young children's everyday experiences—0
Scaling up Multi-domain Semantic Segmentation with Sentence Embeddings—0
ThermalDiffusion: Visual-to-Thermal Image-to-Image Translation for Autonomous Navigation—0
The RoboDrive Challenge: Drive Anytime Anywhere in Any Condition—0
The Second Monocular Depth Estimation Challenge—0
The Surprising Effectiveness of Diffusion Models for Optical Flow and Monocular Depth Estimation—0
-MRF: Capturing Spatial and Semantic Structure in the Parameters for Scene Understanding—0
The Third Monocular Depth Estimation Challenge—0
THIRDEYE: Cue-Aware Monocular Depth Estimation via Brain-Inspired Multi-Stage Fusion—0
TiDy-PSFs: Computational Imaging with Time-Averaged Dynamic Point-Spread-Functions—0
Time-to-Label: Temporal Consistency for Self-Supervised Monocular 3D Object Detection—0
To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation—0
ToDER: Towards Colonoscopy Depth Estimation and Reconstruction with Geometry Constraint Adaptation—0
Token Transforming: A Unified and Training-Free Token Compression Framework for Vision Transformer Acceleration—0
ToSA: Token Selective Attention for Efficient Vision Transformers—0
Total Variation-Based Dense Depth from Multi-Camera Array—0
Touch-GS: Visual-Tactile Supervised 3D Gaussian Splatting—0
Toward Accurate Camera-based 3D Object Detection via Cascade Depth Estimation and Calibration—0
Toward Better SSIM Loss for Unsupervised Monocular Depth Estimation—0
Toward Depth Estimation Using Mask-Based Lensless Cameras—0
Toward Real-world BEV Perception: Depth Uncertainty Estimation via Gaussian Splatting—0
Towards Abdominal 3-D Scene Rendering from Laparoscopy Surgical Videos using NeRFs—0
Towards an AI-based Early Warning System for Bridge Scour—0
Towards Augmented Reality-based Suturing in Monocular Laparoscopic Training—0
Monocular Outdoor Semantic Mapping with a Multi-task Network—0
Towards Comprehensive Representation Enhancement in Semantics-guided Self-supervised Monocular Depth Estimation—0
Towards Depth Foundation Model: Recent Trends in Vision-Based Depth Estimation—0
Towards Domain Generalization for Multi-view 3D Object Detection in Bird-Eye-View—0
Show:102550
← PrevPage 26 of 50Next →
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