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 101–150 of 2454 papers

TitleStatusHype
MonoCD: Monocular 3D Object Detection with Complementary DepthsCode2
Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous DrivingCode2
Robust Shape Fitting for 3D Scene AbstractionCode2
Adaptive Fusion of Single-View and Multi-View Depth for Autonomous DrivingCode2
Kick Back & Relax++: Scaling Beyond Ground-Truth Depth with SlowTV & CribsTVCode2
Depth Information Assisted Collaborative Mutual Promotion Network for Single Image DehazingCode2
X-maps: Direct Depth Lookup for Event-based Structured Light SystemsCode2
Surgical-DINO: Adapter Learning of Foundation Models for Depth Estimation in Endoscopic SurgeryCode2
RadarCam-Depth: Radar-Camera Fusion for Depth Estimation with Learned Metric ScaleCode2
OccNeRF: Advancing 3D Occupancy Prediction in LiDAR-Free EnvironmentsCode2
GPS-Gaussian: Generalizable Pixel-wise 3D Gaussian Splatting for Real-time Human Novel View SynthesisCode2
Depth-Regularized Optimization for 3D Gaussian Splatting in Few-Shot ImagesCode2
SelfOcc: Self-Supervised Vision-Based 3D Occupancy PredictionCode2
RoboDepth: Robust Out-of-Distribution Depth Estimation under CorruptionsCode2
InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision GeneralistsCode2
DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion ModelsCode2
NeRF-Det: Learning Geometry-Aware Volumetric Representation for Multi-View 3D Object DetectionCode2
The RoboDepth Challenge: Methods and Advancements Towards Robust Depth EstimationCode2
Towards Zero-Shot Scale-Aware Monocular Depth EstimationCode2
CompletionFormer: Depth Completion with Convolutions and Vision TransformersCode2
Joint 2D-3D Multi-Task Learning on Cityscapes-3D: 3D Detection, Segmentation, and Depth EstimationCode2
EA-LSS: Edge-aware Lift-splat-shot Framework for 3D BEV Object DetectionCode2
DDP: Diffusion Model for Dense Visual PredictionCode2
A Simple Framework for 3D Occupancy Estimation in Autonomous DrivingCode2
DiffusionDepth: Diffusion Denoising Approach for Monocular Depth EstimationCode2
Unleashing Text-to-Image Diffusion Models for Visual PerceptionCode2
Self-Supervised Learning from Images with a Joint-Embedding Predictive ArchitectureCode2
Behind the Scenes: Density Fields for Single View ReconstructionCode2
GeoMVSNet: Learning Multi-View Stereo With Geometry PerceptionCode2
SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance FieldsCode2
SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map GenerationCode2
Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth EstimationCode2
SC-DepthV3: Robust Self-supervised Monocular Depth Estimation for Dynamic ScenesCode2
CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View CompletionCode2
Map-free Visual Relocalization: Metric Pose Relative to a Single ImageCode2
BEVStereo: Enhancing Depth Estimation in Multi-view 3D Object Detection with Dynamic Temporal StereoCode2
Depth Field Networks for Generalizable Multi-view Scene RepresentationCode2
Monocular 3D Object Detection with Depth from MotionCode2
Towards Scale-Aware, Robust, and Generalizable Unsupervised Monocular Depth Estimation by Integrating IMU Motion DynamicsCode2
BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object DetectionCode2
Single-View View Synthesis in the Wild with Learned Adaptive Multiplane ImagesCode2
MUTR3D: A Multi-camera Tracking Framework via 3D-to-2D QueriesCode2
SurroundDepth: Entangling Surrounding Views for Self-Supervised Multi-Camera Depth EstimationCode2
MultiMAE: Multi-modal Multi-task Masked AutoencodersCode2
BinsFormer: Revisiting Adaptive Bins for Monocular Depth EstimationCode2
NeW CRFs: Neural Window Fully-connected CRFs for Monocular Depth EstimationCode2
A Survey on RGB-D DatasetsCode2
Rethinking Depth Estimation for Multi-View Stereo: A Unified RepresentationCode2
360MonoDepth: High-Resolution 360deg Monocular Depth EstimationCode2
Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution MergingCode2
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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