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 21512200 of 2454 papers

TitleStatusHype
TriDepth: Triangular Patch-based Deep Depth Prediction0
Learn Stereo, Infer Mono: Siamese Networks for Self-Supervised, Monocular, Depth EstimationCode0
Structured Prediction using cGANs with Fusion Discriminator0
DeepPerimeter: Indoor Boundary Estimation from Posed Monocular Sequences0
Learning the Depths of Moving People by Watching Frozen People0
Web Stereo Video Supervision for Depth Prediction from Dynamic Scenes0
Student Becoming the Master: Knowledge Amalgamation for Joint Scene Parsing, Depth Estimation, and More0
A Large RGB-D Dataset for Semi-supervised Monocular Depth Estimation0
Deep Optics for Monocular Depth Estimation and 3D Object Detection0
Online Adaptation through Meta-Learning for Stereo Depth Estimation0
Multi-Scale Geometric Consistency Guided Multi-View Stereo0
Recurrent Neural Network for (Un-)supervised Learning of Monocular VideoVisual Odometry and DepthCode0
PIV-Based 3D Fluid Flow Reconstruction Using Light Field Camera0
Multi-View Stereo by Temporal Nonparametric FusionCode0
Absolute Human Pose Estimation with Depth Prediction NetworkCode0
Learning Single Camera Depth Estimation using Dual-PixelsCode0
Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown CamerasCode0
Non-Lambertian Surface Shape and Reflectance Reconstruction Using Concentric Multi-Spectral Light Field0
Learning Across Tasks and DomainsCode0
Learning monocular depth estimation infusing traditional stereo knowledgeCode0
Visualization of Convolutional Neural Networks for Monocular Depth EstimationCode0
Learning to Adapt for StereoCode0
Geometry-Aware Symmetric Domain Adaptation for Monocular Depth EstimationCode0
CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View DepthCode0
Defogging Kinect: Simultaneous Estimation of Object Region and Depth in Foggy Scenes0
Synthesizing a 4D Spatio-Angular Consistent Light Field from a Single Image0
Veritatem Dies Aperit- Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding ApproachCode0
Low Power Depth Estimation of Rigid Objects for Time-of-Flight Imaging0
Monocular 3D Object Detection with Pseudo-LiDAR Point CloudCode0
Sparse2Dense: From direct sparse odometry to dense 3D reconstruction0
A Novel Monocular Disparity Estimation Network with Domain Transformation and Ambiguity Learning0
Bilateral Cyclic Constraint and Adaptive Regularization for Unsupervised Monocular Depth PredictionCode0
DFineNet: Ego-Motion Estimation and Depth Refinement from Sparse, Noisy Depth Input with RGB Guidance0
Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation0
Structured Knowledge Distillation for Dense PredictionCode0
A Unified Formulation for Visual Odometry0
FastDepth: Fast Monocular Depth Estimation on Embedded SystemsCode0
Self-supervised Learning for Single View Depth and Surface Normal Estimation0
SweepNet: Wide-baseline Omnidirectional Depth EstimationCode0
Region Deformer Networks for Unsupervised Depth Estimation from Unconstrained Monocular VideosCode0
Dead Time Compensation for High-Flux Ranging0
Dense Depth Estimation in Monocular Endoscopy with Self-supervised Learning MethodsCode0
Sparse and noisy LiDAR completion with RGB guidance and uncertaintyCode0
Sparse and noisy LiDAR completion with RGB guidance anduncertaintyCode0
Dense Depth Estimation of a Complex Dynamic Scene without Explicit 3D Motion Estimation0
NeurAll: Towards a Unified Visual Perception Model for Automated Driving0
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
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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