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 751–800 of 2454 papers

TitleStatusHype
Dense Depth from Event Focal Stack—0
Black-box Adversarial Attacks on Monocular Depth Estimation Using Evolutionary Multi-objective Optimization—0
Amodal Depth Anything: Amodal Depth Estimation in the Wild—0
A Compromise Principle in Deep Monocular Depth Estimation—0
Delving into the Pre-training Paradigm of Monocular 3D Object Detection—0
DELTAR: Depth Estimation from a Light-weight ToF Sensor and RGB Image—0
DELTA: Dense Depth from Events and LiDAR using Transformer's Attention—0
DeLiRa: Self-Supervised Depth, Light, and Radiance Fields—0
DejaVu: Conditional Regenerative Learning to Enhance Dense Prediction—0
DEHRFormer: Real-time Transformer for Depth Estimation and Haze Removal from Varicolored Haze Scenes—0
AltNeRF: Learning Robust Neural Radiance Field via Alternating Depth-Pose Optimization—0
A comprehensive survey on recent deep learning-based methods applied to surgical data—0
3D Gaze Tracking for Studying Collaborative Interactions in Mixed-Reality Environments—0
Defogging Kinect: Simultaneous Estimation of Object Region and Depth in Foggy Scenes—0
Deflating Dataset Bias Using Synthetic Data Augmentation—0
GenDepth: Generalizing Monocular Depth Estimation for Arbitrary Camera Parameters via Ground Plane Embedding—0
Generalized Face Anti-Spoofing via Multi-Task Learning and One-Side Meta Triplet Loss—0
DeepWheel: Generating a 3D Synthetic Wheel Dataset for Design and Performance Evaluation—0
Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry—0
Beyond Visual Field of View: Perceiving 3D Environment with Echoes and Vision—0
Gaze-Vergence-Controlled See-Through Vision in Augmented Reality—0
Beyond Inference: Performance Analysis of DNN Server Overheads for Computer Vision—0
A Compact Light Field Camera for Real-Time Depth Estimation—0
All-day Depth Completion—0
3DFS: Deformable Dense Depth Fusion and Segmentation for Object Reconstruction from a Handheld Camera—0
Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding—0
Deep Robotic Prediction with hierarchical RGB-D Fusion—0
DeepRelativeFusion: Dense Monocular SLAM using Single-Image Relative Depth Prediction—0
Deep Planar Parallax for Monocular Depth Estimation—0
Beyond Appearance: Geometric Cues for Robust Video Instance Segmentation—0
Deep Phase Coded Image Prior—0
BEVStereo++: Accurate Depth Estimation in Multi-view 3D Object Detection via Dynamic Temporal Stereo—0
Deep Optics for Monocular Depth Estimation and 3D Object Detection—0
Constructive Universal Approximation and Finite Sample Memorization by Narrow Deep ReLU Networks—0
Align3R: Aligned Monocular Depth Estimation for Dynamic Videos—0
A Compacted Structure for Cross-domain learning on Monocular Depth and Flow Estimation—0
Generalizing Interactive Backpropagating Refinement for Dense Prediction Networks—0
Generic Perceptual Loss for Modeling Structured Output Dependencies—0
Deep Neural Networks for Accurate Depth Estimation with Latent Space Features—0
Deep multi-scale architectures for monocular depth estimation—0
Deep Monocular 3D Human Pose Estimation via Cascaded Dimension-Lifting—0
DeepMetricEye: Metric Depth Estimation in Periocular VR Imagery—0
A learning-based view extrapolation method for axial super-resolution—0
Achieving Domain Robustness in Stereo Matching Networks by Removing Shortcut Learning—0
Gated Stereo: Joint Depth Estimation from Gated and Wide-Baseline Active Stereo Cues—0
DeepLens: Shallow Depth Of Field From A Single Image—0
Deep Learning with Cinematic Rendering: Fine-Tuning Deep Neural Networks Using Photorealistic Medical Images—0
BetterDepth: Plug-and-Play Diffusion Refiner for Zero-Shot Monocular Depth Estimation—0
Deep-Learning-Based Single-Image Height Reconstruction from Very-High-Resolution SAR Intensity Data—0
A Large RGB-D Dataset for Semi-supervised Monocular Depth Estimation—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