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 2251–2300 of 2454 papers

TitleStatusHype
MonoMM: A Multi-scale Mamba-Enhanced Network for Real-time Monocular 3D Object Detection—0
MonoMobility: Zero-Shot 3D Mobility Analysis from Monocular Videos—0
MonoPCC: Photometric-invariant Cycle Constraint for Monocular Depth Estimation of Endoscopic Images—0
MonoPGC: Monocular 3D Object Detection with Pixel Geometry Contexts—0
MonoPP: Metric-Scaled Self-Supervised Monocular Depth Estimation by Planar-Parallax Geometry in Automotive Applications—0
MonoSelfRecon: Purely Self-Supervised Explicit Generalizable 3D Reconstruction of Indoor Scenes from Monocular RGB Views—0
MonSter: Awakening the Mono in Stereo—0
Motion Guided LIDAR-camera Self-calibration and Accelerated Depth Upsampling for Autonomous Vehicles—0
MOTSLAM: MOT-assisted monocular dynamic SLAM using single-view depth estimation—0
Moving SLAM: Fully Unsupervised Deep Learning in Non-Rigid Scenes—0
MSDPN: Monocular Depth Prediction with Partial Laser Observation using Multi-stage Neural Networks—0
MSFNet:Multi-scale features network for monocular depth estimation—0
MSS-DepthNet: Depth Prediction with Multi-Step Spiking Neural Network—0
MT3DNet: Multi-Task learning Network for 3D Surgical Scene Reconstruction—0
Multi-Camera Calibration Free BEV Representation for 3D Object Detection—0
Multi-Camera Collaborative Depth Prediction via Consistent Structure Estimation—0
MultiDepth: Multi-Sample Priors for Refining Monocular Metric Depth Estimations in Indoor Scenes—0
Multi-Frame Self-Supervised Depth Estimation with Multi-Scale Feature Fusion in Dynamic Scenes—0
Multi-Frame Self-Supervised Depth with Transformers—0
MultiGO: Towards Multi-level Geometry Learning for Monocular 3D Textured Human Reconstruction—0
BEVUDA: Multi-geometric Space Alignments for Domain Adaptive BEV 3D Object Detection—0
Multi-Modal Depth Estimation Using Convolutional Neural Networks—0
Multimodal End-to-End Autonomous Driving—0
Multi-Modality Driven LoRA for Adverse Condition Depth Estimation—0
Multi-Object Discovery by Low-Dimensional Object Motion—0
MonoNeRF: Learning Generalizable NeRFs from Monocular Videos without Camera Pose—0
Multi-Robot Collaborative Perception with Graph Neural Networks—0
Gated Cross-Attention Network for Depth Completion—0
MultiTask-CenterNet (MCN): Efficient and Diverse Multitask Learning using an Anchor Free Approach—0
Multi-task human analysis in still images: 2D/3D pose, depth map, and multi-part segmentation—0
Multi-Task Learning-Enabled Automatic Vessel Draft Reading for Intelligent Maritime Surveillance—0
Multi-task Learning for Real-time Autonomous Driving Leveraging Task-adaptive Attention Generator—0
Multi-task learning from fixed-wing UAV images for 2D/3D city modeling—0
Multi-task learning with cross-task consistency for improved depth estimation in colonoscopy—0
Multi-Task Learning with Knowledge Distillation for Dense Prediction—0
Multi-Task Self-Supervised Learning for Image Segmentation Task—0
Multi-task Self-Supervised Visual Learning—0
Multi-View Depth Consistent Image Generation Using Generative AI Models: Application on Architectural Design of University Buildings—0
Multi-View Reconstruction using Signed Ray Distance Functions (SRDF)—0
Multi-view Reconstruction via SfM-guided Monocular Depth Estimation—0
Mutual Adaptive Reasoning for Monocular 3D Multi-Person Pose Estimation—0
MVD-Fusion: Single-view 3D via Depth-consistent Multi-view Generation—0
MV-ROPE: Multi-view Constraints for Robust Category-level Object Pose and Size Estimation—0
MVSAnywhere: Zero-Shot Multi-View Stereo—0
MVS-GS: High-Quality 3D Gaussian Splatting Mapping via Online Multi-View Stereo—0
MVTrans: Multi-View Perception of Transparent Objects—0
Towards Comprehensive Monocular Depth Estimation: Multiple Heads Are Better Than One—0
NeRFmentation: NeRF-based Augmentation for Monocular Depth Estimation—0
NeRFReN: Neural Radiance Fields with Reflections—0
NeRF-VO: Real-Time Sparse Visual Odometry with Neural Radiance Fields—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