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 2101–2150 of 2454 papers

TitleStatusHype
Robust Object Detection with Multi-input Multi-output Faster R-CNN—0
Robust Pseudo Random Fields for Light-Field Stereo Matching—0
Robust Self-Supervised Extrinsic Self-Calibration—0
Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances—0
Robust Vision Using Retro Reflective Markers for Remote Handling in ITER—0
Learning Generalized Visual Odometry Using Position-Aware Optical Flow and Geometric Bundle Adjustment—0
ROIFormer: Semantic-Aware Region of Interest Transformer for Efficient Self-Supervised Monocular Depth Estimation—0
RRNet: Repetition-Reduction Network for Energy Efficient Decoder of Depth Estimation—0
RS-DFM: A Remote Sensing Distributed Foundation Model for Diverse Downstream Tasks—0
RSGaussian:3D Gaussian Splatting with LiDAR for Aerial Remote Sensing Novel View Synthesis—0
RSRD: A Road Surface Reconstruction Dataset and Benchmark for Safe and Comfortable Autonomous Driving—0
RGB-Thermal Infrared Fusion for Robust Depth Estimation in Complex Environments—0
Real-time Monocular Depth Estimation on Embedded Systems—0
S^2-Diffusion: Generalizing from Instance-level to Category-level Skills in Robot Manipulation—0
S^2M^2: Scalable Stereo Matching Model for Reliable Depth Estimation—0
S^2Net: Accurate Panorama Depth Estimation on Spherical Surface—0
S^3: Learnable Sparse Signal Superdensity for Guided Depth Estimation—0
S3: Learnable Sparse Signal Superdensity for Guided Depth Estimation—0
S^3Net: Semantic-Aware Self-supervised Depth Estimation with Monocular Videos and Synthetic Data—0
S³Net: Semantic-Aware Self-supervised Depth Estimation with Monocular Videos and Synthetic Data—0
SAAM: Stealthy Adversarial Attack on Monocular Depth Estimation—0
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional ArchitectureCode0
Precision Aquaculture: An Integrated Computer Vision and IoT Approach for Optimized Tilapia FeedingCode0
CNN-SVO: Improving the Mapping in Semi-Direct Visual Odometry Using Single-Image Depth PredictionCode0
Point Spread Function Estimation of DefocusCode0
Absolute Human Pose Estimation with Depth Prediction NetworkCode0
Depth self-supervision for single image novel view synthesisCode0
Depth Prompting for Sensor-Agnostic Depth EstimationCode0
CNN-SLAM: Real-time dense monocular SLAM with learned depth predictionCode0
Pose Constraints for Consistent Self-supervised Monocular Depth and Ego-motionCode0
Plugging Self-Supervised Monocular Depth into Unsupervised Domain Adaptation for Semantic SegmentationCode0
3D-SiamMask: Vision-Based Multi-Rotor Aerial-Vehicle Tracking for a Moving ObjectCode0
Progressive Fusion for Unsupervised Binocular Depth Estimation using Cycled NetworksCode0
Towards Continual, Online, Self-Supervised DepthCode0
Towards Cross-View-Consistent Self-Supervised Surround Depth EstimationCode0
Plug-and-Play: Improve Depth Estimation via Sparse Data PropagationCode0
Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular VideosCode0
Harnessing Multi-View Perspective of Light Fields for Low-Light ImagingCode0
Asynchronous Collaborative Graph Representation for Frames and EventsCode0
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous DrivingCode0
Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown CamerasCode0
PlaneNet: Piece-wise Planar Reconstruction from a Single RGB ImageCode0
Pseudo RGB-D for Self-Improving Monocular SLAM and Depth PredictionCode0
Planar Prior Assisted PatchMatch Multi-View StereoCode0
Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature ReconstructionCode0
ClearGrasp: 3D Shape Estimation of Transparent Objects for ManipulationCode0
PU-Ray: Domain-Independent Point Cloud Upsampling via Ray Marching on Neural Implicit SurfaceCode0
3DDX: Bone Surface Reconstruction from a Single Standard-Geometry Radiograph via Dual-Face Depth EstimationCode0
Hard Pixel Mining for Depth Privileged Semantic SegmentationCode0
Pyramid Multi-view Stereo Net with Self-adaptive View AggregationCode0
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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