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 351–400 of 2454 papers

TitleStatusHype
All in Tokens: Unifying Output Space of Visual Tasks via Soft TokenCode1
OmniVidar: Omnidirectional Depth Estimation From Multi-Fisheye ImagesCode1
Depth Estimation From Indoor Panoramas With Neural Scene RepresentationCode1
LightedDepth: Video Depth Estimation in Light of Limited Inference View AnglesCode1
CL-MVSNet: Unsupervised Multi-View Stereo with Dual-Level Contrastive LearningCode1
Self-supervised Monocular Underwater Depth Recovery, Image Restoration, and a Real-sea Video DatasetCode1
Trap Attention: Monocular Depth Estimation With Manual TrapsCode1
Energy-Efficient Adaptive 3D SensingCode1
MaskingDepth: Masked Consistency Regularization for Semi-supervised Monocular Depth EstimationCode1
Scene-aware Egocentric 3D Human Pose EstimationCode1
DAG: Depth-Aware Guidance with Denoising Diffusion Probabilistic ModelsCode1
Are We Ready for Vision-Centric Driving Streaming Perception? The ASAP BenchmarkCode1
Towards Practical Plug-and-Play Diffusion ModelsCode1
Mind The Edge: Refining Depth Edges in Sparsely-Supervised Monocular Depth EstimationCode1
Multi-resolution Monocular Depth Map Fusion by Self-supervised Gradient-based CompositionCode1
BEV-LGKD: A Unified LiDAR-Guided Knowledge Distillation Framework for BEV 3D Object DetectionCode1
Self-Supervised Surround-View Depth Estimation with Volumetric Feature FusionCode1
3DPPE: 3D Point Positional Encoding for Multi-Camera 3D Object Detection TransformersCode1
AeDet: Azimuth-invariant Multi-view 3D Object DetectionCode1
The Monocular Depth Estimation ChallengeCode1
A Practical Stereo Depth System for Smart GlassesCode1
BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object DetectionCode1
LightDepth: A Resource Efficient Depth Estimation Approach for Dealing with Ground Truth Sparsity via Curriculum LearningCode1
RCDPT: Radar-Camera fusion Dense Prediction TransformerCode1
Context-Enhanced Stereo TransformerCode1
Event-based Stereo Depth Estimation from Ego-motion using Ray Density FusionCode1
Attention Attention Everywhere: Monocular Depth Prediction with Skip AttentionCode1
Frequency-Aware Self-Supervised Monocular Depth EstimationCode1
Detaching and Boosting: Dual Engine for Scale-Invariant Self-Supervised Monocular Depth EstimationCode1
Image Masking for Robust Self-Supervised Monocular Depth EstimationCode1
PlaneDepth: Self-supervised Depth Estimation via Orthogonal PlanesCode1
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier ConvolutionsCode1
Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuningCode1
Self-Supervised Monocular Depth Estimation: Solving the Edge-Fattening ProblemCode1
CrossDTR: Cross-view and Depth-guided Transformers for 3D Object DetectionCode1
SAPA: Similarity-Aware Point Affiliation for Feature UpsamplingCode1
UDepth: Fast Monocular Depth Estimation for Visually-guided Underwater RobotsCode1
3D-PL: Domain Adaptive Depth Estimation with 3D-aware Pseudo-LabelingCode1
TODE-Trans: Transparent Object Depth Estimation with TransformerCode1
SF2SE3: Clustering Scene Flow into SE(3)-Motions via Proposal and SelectionCode1
Self-distilled Feature Aggregation for Self-supervised Monocular Depth EstimationCode1
DevNet: Self-supervised Monocular Depth Learning via Density Volume ConstructionCode1
A Benchmark and a Baseline for Robust Multi-view Depth EstimationCode1
BiFuse++: Self-supervised and Efficient Bi-projection Fusion for 360 Depth EstimationCode1
LiteDepth: Digging into Fast and Accurate Depth Estimation on Mobile DevicesCode1
Synthehicle: Multi-Vehicle Multi-Camera Tracking in Virtual CitiesCode1
Depth Map Decomposition for Monocular Depth EstimationCode1
Learning an Efficient Multimodal Depth Completion ModelCode1
Learning Sub-Pixel Disparity Distribution for Light Field Depth EstimationCode1
Net2Brain: A Toolbox to compare artificial vision models with human brain responsesCode1
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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