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 1601–1650 of 2454 papers

TitleStatusHype
Improving Bird's Eye View Semantic Segmentation by Task Decomposition—0
Improving Depth Gradient Continuity in Transformers: A Comparative Study on Monocular Depth Estimation with CNN—0
Improving Distant 3D Object Detection Using 2D Box Supervision—0
Improving Domain Generalization in Self-supervised Monocular Depth Estimation via Stabilized Adversarial Training—0
Improving Geometric Consistency for 360-Degree Neural Radiance Fields in Indoor Scenarios—0
Improving Monocular Depth Estimation by Leveraging Structural Awareness and Complementary Datasets—0
Improving Monocular Visual Odometry Using Learned Depth—0
Improving Online Performance Prediction for Semantic Segmentation—0
Improving Pixel-Level Contrastive Learning by Leveraging Exogenous Depth Information—0
Improving the Reliability for Confidence Estimation—0
Increased-Range Unsupervised Monocular Depth Estimation—0
Incremental Joint Learning of Depth, Pose and Implicit Scene Representation on Monocular Camera in Large-scale Scenes—0
In defense of OSVOS—0
Independent Component Alignment for Multi-Task Learning—0
Indoor Layout Estimation by 2D LiDAR and Camera Fusion—0
Indoor Scene Structure Analysis for Single Image Depth Estimation—0
Inferring Point Clouds from Single Monocular Images by Depth Intermediation—0
Input-level Inductive Biases for 3D Reconstruction—0
InseRF: Text-Driven Generative Object Insertion in Neural 3D Scenes—0
In-situ and Non-contact Etch Depth Prediction in Plasma Etching via Machine Learning (ANN & BNN) and Digital Image Colorimetry—0
Instance-aware Multi-Camera 3D Object Detection with Structural Priors Mining and Self-Boosting Learning—0
Instance-aware multi-object self-supervision for monocular depth prediction—0
Instance-Level Task Parameters: A Robust Multi-task Weighting Framework—0
Instantaneous Stereo Depth Estimation of Real-World Stimuli with a Neuromorphic Stereo-Vision Setup—0
Interpretable Action Recognition on Hard to Classify Actions—0
Into the Twilight Zone: Depth Estimation using Joint Structure-Stereo Optimization—0
Intrinsic Depth: Improving Depth Transfer With Intrinsic Images—0
Intrinsic Image Decomposition for Robust Self-supervised Monocular Depth Estimation on Reflective Surfaces—0
Physics-Inspired Deep Learning and Transferable Models for Bridge Scour Prediction—0
Invisible Stitch: Generating Smooth 3D Scenes with Depth Inpainting—0
Is my Depth Ground-Truth Good Enough? HAMMER -- Highly Accurate Multi-Modal Dataset for DEnse 3D Scene Regression—0
Iterative Occlusion-Aware Light Field Depth Estimation using 4D Geometrical Cues—0
Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions—0
Jamais Vu: Exposing the Generalization Gap in Supervised Semantic Correspondence—0
Jasmine: Harnessing Diffusion Prior for Self-supervised Depth Estimation—0
J-MOD^2: Joint Monocular Obstacle Detection and Depth Estimation—0
Joint 3D Layout and Depth Prediction from a Single Indoor Panorama Image—0
Joint Blind Motion Deblurring and Depth Estimation of Light Field—0
Joint Depth Estimation and Camera Shake Removal from Single Blurry Image—0
Joint Depth Prediction and Semantic Segmentation with Multi-View SAM—0
JointDistill: Adaptive Multi-Task Distillation for Joint Depth Estimation and Scene Segmentation—0
JointDiT: Enhancing RGB-Depth Joint Modeling with Diffusion Transformers—0
Joint Graph-based Depth Refinement and Normal Estimation—0
Joint Hand-object 3D Reconstruction from a Single Image with Cross-branch Feature Fusion—0
Joint Image and Depth Estimation with Mask-Based Lensless Cameras—0
Joint Learning of Frequency and Spatial Domains for Dense Predictions—0
JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling—0
Joint Optimization of Neural Radiance Fields and Continuous Camera Motion from a Monocular Video—0
Joint Prediction of Monocular Depth and Structure using Planar and Parallax Geometry—0
Joint Pruning & Quantization for Extremely Sparse Neural Networks—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