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

Showing 21762200 of 2454 papers

TitleStatusHype
GEN-SLAM: Generative Modeling for Monocular Simultaneous Localization and Mapping0
Unstructured Multi-View Depth Estimation Using Mask-Based Multiplane RepresentationCode0
Fully Convolutional Networks for Monocular Retinal Depth Estimation and Optic Disc-Cup Segmentation0
Attention-based Context Aggregation Network for Monocular Depth EstimationCode0
Fast and Efficient Lenslet Image Compression0
Monocular Depth Estimation: A Survey0
Unsupervised Learning-based Depth Estimation aided Visual SLAM Approach0
AuxNet: Auxiliary tasks enhanced Semantic Segmentation for Automated Driving0
Monocular Outdoor Semantic Mapping with a Multi-task Network0
NRMVS: Non-Rigid Multi-View Stereo0
Real-time Joint Object Detection and Semantic Segmentation Network for Automated Driving0
Exploring Deep Spiking Neural Networks for Automated Driving Applications0
Unsupervised Learning of Depth and Ego-Motion from Cylindrical Panoramic VideoCode1
Unsupervised monocular stereo matching0
High Quality Monocular Depth Estimation via Transfer LearningCode1
Wireless Software Synchronization of Multiple Distributed Cameras0
Plug-and-Play: Improve Depth Estimation via Sparse Data PropagationCode0
Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous DrivingCode1
Fast and Accurate Depth Estimation from Sparse Light Fields0
Learning Common Representation from RGB and Depth Images0
SIGNet: Semantic Instance Aided Unsupervised 3D Geometry PerceptionCode0
Learning Semantic Segmentation from Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach0
DeepV2D: Video to Depth with Differentiable Structure from MotionCode0
Unsupervised Learning of Monocular Depth Estimation with Bundle Adjustment, Super-Resolution and Clip Loss0
Learning to Infer the Depth Map of a Hand from its Color Image0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OmniDepthRMSE0.62Unverified
2SphereDepthRMSE0.45Unverified
3Jin et al.RMSE0.42Unverified
4BiFuse with fusionRMSE0.41Unverified
5HoHoNet (ResNet-101)RMSE0.38Unverified
6PanoDepthRMSE0.37Unverified
7BiFuse++RMSE0.37Unverified
8UniFuse with fusionRMSE0.37Unverified
9DisConvRMSE0.37Unverified
10SliceNetRMSE0.37Unverified
#ModelMetricClaimedVerifiedStatus
1A2JmAP8.61Unverified
2PAD-NetRMS0.79Unverified
3MS-CRFRMS0.59Unverified
4DORNRMS0.51Unverified
5FreeformRMS0.43Unverified
6Optimized, freeformRMS0.43Unverified
7VNLRMS0.42Unverified
8BTSRMS0.41Unverified
9TransDepth (AGD+ ViT)RMS0.37Unverified
10AdaBinsRMS0.36Unverified
#ModelMetricClaimedVerifiedStatus
1T2NetAbs Rel0.35Unverified
2MIDASAbs Rel0.31Unverified
3Bhattacharjee et al.Abs Rel0.25Unverified
#ModelMetricClaimedVerifiedStatus
1T2NetAbs Rel0.49Unverified
2MIDASAbs Rel0.42Unverified
3Bhattacharjee et al.Abs Rel0.38Unverified
#ModelMetricClaimedVerifiedStatus
1LeReSabsolute relative error0.1Unverified
2DELTASabsolute relative error0.09Unverified
3Distill Any Depthabsolute relative error0.04Unverified
#ModelMetricClaimedVerifiedStatus
1SDC-DepthRMSE6.92Unverified
2SwinMTLRMSE6.35Unverified
#ModelMetricClaimedVerifiedStatus
1AIP-BrownDelta < 1.250.36Unverified
2LeResDelta < 1.250.23Unverified
#ModelMetricClaimedVerifiedStatus
1H-Net (Ours)Absolute relative error (AbsRel)0.09Unverified
2H-Net (Ours) Full EigenAbsolute relative error (AbsRel)0.08Unverified
#ModelMetricClaimedVerifiedStatus
1GLPDepthDelta < 1.250.43Unverified
2SRDINET (Model A)Delta < 1.250.4Unverified
#ModelMetricClaimedVerifiedStatus
1Atlas (finetuned)RMSE0.17Unverified
2Atlas (plain)RMSE0.17Unverified
#ModelMetricClaimedVerifiedStatus
1LFattNetBadPix(0.01)17.23Unverified
#ModelMetricClaimedVerifiedStatus
1LightDepthNumber of parameters (M)42.6Unverified
#ModelMetricClaimedVerifiedStatus
1UniFuseAbs Rel0.11Unverified
#ModelMetricClaimedVerifiedStatus
1X-TC (Cross-Task Consistency)L1 error1.63Unverified