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 951–1000 of 2454 papers

TitleStatusHype
Video Depth without Video Models—0
SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation—0
Spatially Visual Perception for End-to-End Robotic Learning—0
Low-rank Adaptation-based All-Weather Removal for Autonomous Navigation—0
DepthCues: Evaluating Monocular Depth Perception in Large Vision Models—0
Generative Omnimatte: Learning to Decompose Video into Layers—0
Gaussian Scenes: Pose-Free Sparse-View Scene Reconstruction using Depth-Enhanced Diffusion Priors—0
PriorDiffusion: Leverage Language Prior in Diffusion Models for Monocular Depth Estimation—0
DATAP-SfM: Dynamic-Aware Tracking Any Point for Robust Structure from Motion in the Wild—0
GPS-Gaussian+: Generalizable Pixel-wise 3D Gaussian Splatting for Real-Time Human-Scene Rendering from Sparse Views—0
MGNiceNet: Unified Monocular Geometric Scene UnderstandingCode0
Scalable Autoregressive Monocular Depth Estimation—0
The ADUULM-360 Dataset -- A Multi-Modal Dataset for Depth Estimation in Adverse WeatherCode0
MetricGold: Leveraging Text-To-Image Latent Diffusion Models for Metric Depth EstimationCode0
Mono2Stereo: Monocular Knowledge Transfer for Enhanced Stereo Matching—0
RenderBender: A Survey on Adversarial Attacks Using Differentiable Rendering—0
Architect: Generating Vivid and Interactive 3D Scenes with Hierarchical 2D Inpainting—0
Scaling Properties of Diffusion Models for Perceptual Tasks—0
SE(3) Equivariant Ray Embeddings for Implicit Multi-View Depth Estimation—0
SimpleBEV: Improved LiDAR-Camera Fusion Architecture for 3D Object Detection—0
D^3epth: Self-Supervised Depth Estimation with Dynamic Mask in Dynamic ScenesCode0
Enhancing Bronchoscopy Depth Estimation through Synthetic-to-Real Domain Adaptation—0
Adaptive Stereo Depth Estimation with Multi-Spectral Images Across All Lighting Conditions—0
Revisiting Disparity from Dual-Pixel Images: Physics-Informed Lightweight Depth Estimation—0
Correlation of Object Detection Performance with Visual Saliency and Depth EstimationCode0
PMPNet: Pixel Movement Prediction Network for Monocular Depth Estimation in Dynamic Scenes—0
FewViewGS: Gaussian Splatting with Few View Matching and Multi-stage Training—0
Improving Domain Generalization in Self-supervised Monocular Depth Estimation via Stabilized Adversarial Training—0
MultiDepth: Multi-Sample Priors for Refining Monocular Metric Depth Estimations in Indoor Scenes—0
Optical Lens Attack on Monocular Depth Estimation for Autonomous Driving—0
Nested ResNet: A Vision-Based Method for Detecting the Sensing Area of a Drop-in Gamma Probe—0
Active Event Alignment for Monocular Distance Estimation—0
Segmentation-aware Prior Assisted Joint Global Information Aggregated 3D Building Reconstruction—0
Retrieving snow depth distribution by downscaling ERA5 Reanalysis with ICESat-2 laser altimetry—0
UnCLe: Unsupervised Continual Learning of Depth Completion—0
YOLO11 and Vision Transformers based 3D Pose Estimation of Immature Green Fruits in Commercial Apple Orchards for Robotic Thinning—0
DH-VTON: Deep Text-Driven Virtual Try-On via Hybrid Attention Learning—0
CVCP-Fusion: On Implicit Depth Estimation for 3D Bounding Box PredictionCode0
Enhanced Encoder-Decoder Architecture for Accurate Monocular Depth EstimationCode0
Improved Depth Estimation of Bayesian Neural NetworksCode0
Color-Guided Flying Pixel Correction in Depth ImagesCode0
Surgical Depth Anything: Depth Estimation for Surgical Scenes using Foundation Models—0
Structure-Centric Robust Monocular Depth Estimation via Knowledge Distillation—0
Analysis of different disparity estimation techniques on aerial stereo image datasets—0
Vision Transformer based Random Walk for Group Re-Identification—0
CUBE360: Learning Cubic Field Representation for Monocular 360 Depth Estimation for Virtual Reality—0
EndoPerfect: High-Accuracy Monocular Depth Estimation and 3D Reconstruction for Endoscopic Surgery via NeRF-Stereo Fusion—0
RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language DescriptionsCode0
Towards Full-parameter and Parameter-efficient Self-learning For Endoscopic Camera Depth Estimation—0
Drone Stereo Vision for Radiata Pine Branch Detection and Distance Measurement: Utilizing Deep Learning and YOLO Integration—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