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 851–875 of 2454 papers

TitleStatusHype
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion—0
Building Rome with Convex Optimization—0
MetaFE-DE: Learning Meta Feature Embedding for Depth Estimation from Monocular Endoscopic Images—0
DOC-Depth: A novel approach for dense depth ground truth generation—0
Leveraging Stable Diffusion for Monocular Depth Estimation via Image Semantic Encoding—0
Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion—0
Snapshot Compressed Imaging Based Single-Measurement Computer Vision for Videos—0
Rethinking Encoder-Decoder Flow Through Shared Structures—0
PromptMono: Cross Prompting Attention for Self-Supervised Monocular Depth Estimation in Challenging Environments—0
IMAGINE-E: Image Generation Intelligence Evaluation of State-of-the-art Text-to-Image ModelsCode0
UniUIR: Considering Underwater Image Restoration as An All-in-One Learner—0
Enhancing Monocular Depth Estimation with Multi-Source Auxiliary TasksCode0
Fast Underwater Scene Reconstruction using Multi-View Stereo and Physical Imaging—0
Survey on Monocular Metric Depth Estimation—0
RDG-GS: Relative Depth Guidance with Gaussian Splatting for Real-time Sparse-View 3D Rendering—0
Multi-Modal Attention Networks for Enhanced Segmentation and Depth Estimation of Subsurface Defects in Pulse ThermographyCode0
Zero-Shot Monocular Scene Flow Estimation in the Wild—0
One-D-Piece: Image Tokenizer Meets Quality-Controllable Compression—0
StereoGen: High-quality Stereo Image Generation from a Single Image—0
Revisiting Birds Eye View Perception Models with Frozen Foundation Models: DINOv2 and Metric3Dv2—0
A Critical Synthesis of Uncertainty Quantification and Foundation Models in Monocular Depth Estimation—0
Matching Free Depth Recovery from Structured Light—0
A Systematic Literature Review on Deep Learning-based Depth Estimation in Computer Vision—0
DPF^*: improved Depth Potential Function for scale-invariant sulcal depth estimationCode0
IGAF: Incremental Guided Attention Fusion for Depth Super-Resolution—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