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 301–350 of 2454 papers

TitleStatusHype
SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation—0
GAPartManip: A Large-scale Part-centric Dataset for Material-Agnostic Articulated Object ManipulationCode5
Helvipad: A Real-World Dataset for Omnidirectional Stereo Depth EstimationCode1
Low-rank Adaptation-based All-Weather Removal for Autonomous Navigation—0
DepthCues: Evaluating Monocular Depth Perception in Large Vision Models—0
Boost 3D Reconstruction using Diffusion-based Monocular Camera CalibrationCode2
Spatially Visual Perception for End-to-End Robotic Learning—0
DROID-Splat: Combining end-to-end SLAM with 3D Gaussian SplattingCode3
Generative Omnimatte: Learning to Decompose Video into Layers—0
One Diffusion to Generate Them AllCode4
PriorDiffusion: Leverage Language Prior in Diffusion Models for Monocular Depth Estimation—0
Gaussian Scenes: Pose-Free Sparse-View Scene Reconstruction using Depth-Enhanced Diffusion Priors—0
OceanLens: An Adaptive Backscatter and Edge Correction using Deep Learning Model for Enhanced Underwater ImagingCode1
DATAP-SfM: Dynamic-Aware Tracking Any Point for Robust Structure from Motion in the Wild—0
Scalable Autoregressive Monocular Depth Estimation—0
GPS-Gaussian+: Generalizable Pixel-wise 3D Gaussian Splatting for Real-Time Human-Scene Rendering from Sparse Views—0
The ADUULM-360 Dataset -- A Multi-Modal Dataset for Depth Estimation in Adverse WeatherCode0
MGNiceNet: Unified Monocular Geometric Scene UnderstandingCode0
MetricGold: Leveraging Text-To-Image Latent Diffusion Models for Metric Depth EstimationCode0
SPARS3R: Semantic Prior Alignment and Regularization for Sparse 3D ReconstructionCode2
Efficient Depth Estimation for Unstable Stereo Camera Systems on AR GlassesCode1
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
OSMLoc: Single Image-Based Visual Localization in OpenStreetMap with Fused Geometric and Semantic GuidanceCode2
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
Enhancing Bronchoscopy Depth Estimation through Synthetic-to-Real Domain Adaptation—0
D^3epth: Self-Supervised Depth Estimation with Dynamic Mask in Dynamic ScenesCode0
Revisiting Disparity from Dual-Pixel Images: Physics-Informed Lightweight Depth Estimation—0
Adaptive Stereo Depth Estimation with Multi-Spectral Images Across All Lighting Conditions—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
On Deep Learning for Geometric and Semantic Scene Understanding Using On-Vehicle 3D LiDARCode2
Optical Lens Attack on Monocular Depth Estimation for Autonomous Driving—0
ImOV3D: Learning Open-Vocabulary Point Clouds 3D Object Detection from Only 2D ImagesCode2
Nested ResNet: A Vision-Based Method for Detecting the Sensing Area of a Drop-in Gamma Probe—0
PF3plat: Pose-Free Feed-Forward 3D Gaussian SplattingCode3
Active Event Alignment for Monocular Distance Estimation—0
MVSDet: Multi-View Indoor 3D Object Detection via Efficient Plane SweepsCode1
Depth Attention for Robust RGB TrackingCode1
Unlocking Comics: The AI4VA Dataset for Visual UnderstandingCode1
MonoDGP: Monocular 3D Object Detection with Decoupled-Query and Geometry-Error PriorsCode2
Segmentation-aware Prior Assisted Joint Global Information Aggregated 3D Building Reconstruction—0
Thermal Chameleon: Task-Adaptive Tone-mapping for Radiometric Thermal-Infrared imagesCode1
Retrieving snow depth distribution by downscaling ERA5 Reanalysis with ICESat-2 laser altimetry—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