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 201–250 of 2454 papers

TitleStatusHype
FoundationStereo: Zero-Shot Stereo MatchingCode7
One-D-Piece: Image Tokenizer Meets Quality-Controllable Compression—0
HSPFormer: Hierarchical Spatial Perception Transformer for Semantic SegmentationCode1
DEFOM-Stereo: Depth Foundation Model Based Stereo MatchingCode3
StereoGen: High-quality Stereo Image Generation from a Single Image—0
MonSter: Marry Monodepth to Stereo Unleashes PowerCode4
Revisiting Birds Eye View Perception Models with Frozen Foundation Models: DINOv2 and Metric3Dv2—0
A Critical Synthesis of Uncertainty Quantification and Foundation Models in Monocular Depth Estimation—0
RePoseD: Efficient Relative Pose Estimation With Known Depth InformationCode1
Matching Free Depth Recovery from Structured Light—0
DPF^*: improved Depth Potential Function for scale-invariant sulcal depth estimationCode0
A Systematic Literature Review on Deep Learning-based Depth Estimation in Computer Vision—0
Relative Pose Estimation through Affine Corrections of Monocular Depth PriorsCode3
Depth Any Camera: Zero-Shot Metric Depth Estimation from Any CameraCode3
DepthMaster: Taming Diffusion Models for Monocular Depth EstimationCode2
SafeAug: Safety-Critical Driving Data Augmentation from Naturalistic Datasets—0
Laparoscopic Scene Analysis for Intraoperative Visualisation of Gamma Probe Signals in Minimally Invasive Cancer Surgery—0
IGAF: Incremental Guided Attention Fusion for Depth Super-Resolution—0
TexAVi: Generating Stereoscopic VR Video Clips from Text Descriptions—0
PatchRefiner V2: Fast and Lightweight Real-Domain High-Resolution Metric Depth Estimation—0
Sea-ing in Low-lightCode0
HUSH: Holistic Panoramic 3D Scene Understanding using Spherical Harmonics—0
Vision-Language Embodiment for Monocular Depth Estimation—0
Rectification-specific Supervision and Constrained Estimator for Online Stereo Rectification—0
Distilling Monocular Foundation Model for Fine-grained Depth Completion—0
BLADE: Single-view Body Mesh Estimation through Accurate Depth Estimation—0
PanDA: Towards Panoramic Depth Anything with Unlabeled Panoramas and Mobius Spatial Augmentation—0
OmniStereo: Real-time Omnidireactional Depth Estimation with Multiview Fisheye CamerasCode1
GeoDepth: From Point-to-Depth to Plane-to-Depth Modeling for Self-Supervised Monocular Depth Estimation—0
Joint Optimization of Neural Radiance Fields and Continuous Camera Motion from a Monocular Video—0
SDGOCC: Semantic and Depth-Guided Bird's-Eye View Transformation for 3D Multimodal Occupancy PredictionCode0
CH3Depth: Efficient and Flexible Depth Foundation Model with Flow Matching—0
Asynchronous Collaborative Graph Representation for Frames and EventsCode0
Learned Binocular-Encoding Optics for RGBD Imaging Using Joint Stereo and Focus Cues—0
Toward Real-world BEV Perception: Depth Uncertainty Estimation via Gaussian Splatting—0
Perceptual Inductive Bias Is What You Need Before Contrastive Learning—0
Improved Monocular Depth Prediction Using Distance Transform Over Pre-semantic Contours with Self-supervised Neural Networks—0
Flowing from Words to Pixels: A Noise-Free Framework for Cross-Modality Evolution—0
MegaSaM: Accurate, Fast and Robust Structure and Motion from Casual Dynamic Videos—0
Tech Report: Divide and Conquer 3D Real-Time Reconstruction for Improved IGS—0
FPGA-based Acceleration of Neural Network for Image Classification using Vitis AI—0
DPBridge: Latent Diffusion Bridge for Dense Prediction—0
MetricDepth: Enhancing Monocular Depth Estimation with Deep Metric Learning—0
Multi-Modality Driven LoRA for Adverse Condition Depth Estimation—0
DepthMamba with Adaptive Fusion—0
Revisiting Monocular 3D Object Detection from Scene-Level Depth Retargeting to Instance-Level Spatial Refinement—0
Learning Monocular Depth from Events via Egomotion Compensation—0
MVS-GS: High-Quality 3D Gaussian Splatting Mapping via Online Multi-View Stereo—0
An End-to-End Depth-Based Pipeline for Selfie Image Rectification—0
HV-BEV: Decoupling Horizontal and Vertical Feature Sampling for Multi-View 3D Object DetectionCode0
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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