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 26–50 of 2454 papers

TitleStatusHype
TR2M: Transferring Monocular Relative Depth to Metric Depth with Language Descriptions and Scale-Oriented ContrastCode1
Test3R: Learning to Reconstruct 3D at Test TimeCode2
Self-Supervised Enhancement for Depth from a Lightweight ToF Sensor with Monocular ImagesCode1
Leveraging 6DoF Pose Foundation Models For Mapping Marine Sediment BurialCode0
DCIRNet: Depth Completion with Iterative Refinement for Dexterous Grasping of Transparent and Reflective Objects—0
EgoM2P: Egocentric Multimodal Multitask Pretraining—0
Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images—0
Hidden in plain sight: VLMs overlook their visual representations—0
Jamais Vu: Exposing the Generalization Gap in Supervised Semantic Correspondence—0
Dark Channel-Assisted Depth-from-Defocus from a Single Image—0
Token Transforming: A Unified and Training-Free Token Compression Framework for Vision Transformer Acceleration—0
Aerial Multi-View Stereo via Adaptive Depth Range Inference and Normal Cues—0
Structure-Aware Radar-Camera Depth Estimation—0
Toward Better SSIM Loss for Unsupervised Monocular Depth Estimation—0
Voyager: Long-Range and World-Consistent Video Diffusion for Explorable 3D Scene Generation—0
Attacking Attention of Foundation Models Disrupts Downstream TasksCode0
Harnessing Foundation Models for Robust and Generalizable 6-DOF Bronchoscopy Localization—0
Ultrafast High-Flux Single-Photon LiDAR Simulator via Neural Mapping—0
Bridging Geometric and Semantic Foundation Models for Generalized Monocular Depth Estimation—0
GeoMan: Temporally Consistent Human Geometry Estimation using Image-to-Video Diffusion—0
Spatial RoboGrasp: Generalized Robotic Grasping Control Policy—0
SpikeStereoNet: A Brain-Inspired Framework for Stereo Depth Estimation from Spike Streams—0
From Single Images to Motion Policies via Video-Generation Environment Representations—0
EvidenceMoE: A Physics-Guided Mixture-of-Experts with Evidential Critics for Advancing Fluorescence Light Detection and Ranging in Scattering Media—0
BadDepth: Backdoor Attacks Against Monocular Depth Estimation in the Physical World—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