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 1451–1500 of 2454 papers

TitleStatusHype
Improving Depth Estimation using Location Information—0
Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth EstimationCode1
High-Accuracy RGB-D Face Recognition via Segmentation-Aware Face Depth Estimation and Mask-Guided Attention Network—0
NVS-MonoDepth: Improving Monocular Depth Prediction with Novel View Synthesis—0
On the Uncertain Single-View Depths in Colonoscopies—0
Consistent Depth Prediction under Various Illuminations using Dilated Cross Attention—0
Multi-View Depth Estimation by Fusing Single-View Depth Probability with Multi-View GeometryCode1
Towards General and Efficient Active LearningCode1
Self-Supervised Monocular Depth and Ego-Motion Estimation in Endoscopy: Appearance Flow to the RescueCode1
Depth Refinement for Improved Stereo Reconstruction—0
VirtualCube: An Immersive 3D Video Communication System—0
GCNDepth: Self-supervised Monocular Depth Estimation based on Graph Convolutional NetworkCode1
Curvature-guided dynamic scale networks for Multi-view StereoCode1
Sparse Depth Completion with Semantic Mesh Deformation Optimization—0
Towards Full-to-Empty Room Generation with Structure-Aware Feature Encoding and Soft Semantic Region-Adaptive Normalization—0
Wild ToFu: Improving Range and Quality of Indirect Time-of-Flight Depth with RGB Fusion in Challenging Environments—0
Self-Supervised Camera Self-Calibration from Video—0
3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video—0
Input-level Inductive Biases for 3D Reconstruction—0
PolyphonicFormer: Unified Query Learning for Depth-aware Video Panoptic SegmentationCode1
Toward Practical Monocular Indoor Depth EstimationCode1
Generalized Binary Search Network for Highly-Efficient Multi-View StereoCode1
Gated2Gated: Self-Supervised Depth Estimation from Gated ImagesCode1
Machine Learning Subsystem for Autonomous Collision Avoidance on a small UAS with Embedded GPU—0
SGM3D: Stereo Guided Monocular 3D Object DetectionCode1
Object-aware Monocular Depth Prediction with Instance ConvolutionsCode1
Efficient Neural Radiance Fields for Interactive Free-viewpoint VideoCode1
Dimensions of Motion: Monocular Prediction through Flow Subspaces—0
A benchmark with decomposed distribution shifts for 360 monocular depth estimationCode1
3DVNet: Multi-View Depth Prediction and Volumetric RefinementCode1
FaSS-MVS -- Fast Multi-View Stereo with Surface-Aware Semi-Global Matching from UAV-borne Monocular Imagery—0
360MonoDepth: High-Resolution 360° Monocular Depth EstimationCode1
NeRFReN: Neural Radiance Fields with Reflections—0
Instance-wise Occlusion and Depth Orders in Natural ScenesCode1
Robust Object Detection with Multi-input Multi-output Faster R-CNN—0
MonoPLFlowNet: Permutohedral Lattice FlowNet for Real-Scale 3D Scene FlowEstimation with Monocular ImagesCode1
SM3D: Simultaneous Monocular Mapping and 3D Detection—0
TriStereoNet: A Trinocular Framework for Multi-baseline Disparity EstimationCode1
Learning Generalized Visual Odometry Using Position-Aware Optical Flow and Geometric Bundle Adjustment—0
ColDE: A Depth Estimation Framework for Colonoscopy Reconstruction—0
LOLNeRF: Learn from One Look—0
SUB-Depth: Self-distillation and Uncertainty Boosting Self-supervised Monocular Depth EstimationCode1
Temporally Consistent Online Depth Estimation in Dynamic Scenes—0
Towards Comprehensive Monocular Depth Estimation: Multiple Heads Are Better Than One—0
Error Diagnosis of Deep Monocular Depth Estimation Models—0
Residual-Guided Learning Representation for Self-Supervised Monocular Depth Estimation—0
Online Mutual Adaptation of Deep Depth Prediction and Visual SLAM—0
Towards Panoptic 3D Parsing for Single Image in the Wild—0
Deep-Learning-Based Single-Image Height Reconstruction from Very-High-Resolution SAR Intensity Data—0
Absolute distance prediction based on deep learning object detection and monocular depth estimation modelsCode1
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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