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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 851–900 of 2454 papers

TitleStatusHype
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion—0
Building Rome with Convex Optimization—0
MetaFE-DE: Learning Meta Feature Embedding for Depth Estimation from Monocular Endoscopic Images—0
DOC-Depth: A novel approach for dense depth ground truth generation—0
Leveraging Stable Diffusion for Monocular Depth Estimation via Image Semantic Encoding—0
Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion—0
Snapshot Compressed Imaging Based Single-Measurement Computer Vision for Videos—0
Rethinking Encoder-Decoder Flow Through Shared Structures—0
PromptMono: Cross Prompting Attention for Self-Supervised Monocular Depth Estimation in Challenging Environments—0
IMAGINE-E: Image Generation Intelligence Evaluation of State-of-the-art Text-to-Image ModelsCode0
Enhancing Monocular Depth Estimation with Multi-Source Auxiliary TasksCode0
UniUIR: Considering Underwater Image Restoration as An All-in-One Learner—0
Fast Underwater Scene Reconstruction using Multi-View Stereo and Physical Imaging—0
Survey on Monocular Metric Depth Estimation—0
RDG-GS: Relative Depth Guidance with Gaussian Splatting for Real-time Sparse-View 3D Rendering—0
One-D-Piece: Image Tokenizer Meets Quality-Controllable Compression—0
Multi-Modal Attention Networks for Enhanced Segmentation and Depth Estimation of Subsurface Defects in Pulse ThermographyCode0
Zero-Shot Monocular Scene Flow Estimation in the Wild—0
StereoGen: High-quality Stereo Image Generation from a Single Image—0
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
Matching Free Depth Recovery from Structured Light—0
A Systematic Literature Review on Deep Learning-based Depth Estimation in Computer Vision—0
DPF^*: improved Depth Potential Function for scale-invariant sulcal depth estimationCode0
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
SafeAug: Safety-Critical Driving Data Augmentation from Naturalistic Datasets—0
TexAVi: Generating Stereoscopic VR Video Clips from Text Descriptions—0
PatchRefiner V2: Fast and Lightweight Real-Domain High-Resolution Metric Depth Estimation—0
BLADE: Single-view Body Mesh Estimation through Accurate Depth Estimation—0
MegaSaM: Accurate, Fast and Robust Structure and Motion from Casual Dynamic Videos—0
HUSH: Holistic Panoramic 3D Scene Understanding using Spherical Harmonics—0
Rectification-specific Supervision and Constrained Estimator for Online Stereo Rectification—0
Sea-ing in Low-lightCode0
GeoDepth: From Point-to-Depth to Plane-to-Depth Modeling for Self-Supervised Monocular Depth Estimation—0
Flowing from Words to Pixels: A Noise-Free Framework for Cross-Modality Evolution—0
Learned Binocular-Encoding Optics for RGBD Imaging Using Joint Stereo and Focus Cues—0
PanDA: Towards Panoramic Depth Anything with Unlabeled Panoramas and Mobius Spatial Augmentation—0
Vision-Language Embodiment for Monocular Depth Estimation—0
Asynchronous Collaborative Graph Representation for Frames and EventsCode0
Perceptual Inductive Bias Is What You Need Before Contrastive Learning—0
Distilling Monocular Foundation Model for Fine-grained Depth Completion—0
CH3Depth: Efficient and Flexible Depth Foundation Model with Flow Matching—0
Joint Optimization of Neural Radiance Fields and Continuous Camera Motion from a Monocular Video—0
Toward Real-world BEV Perception: Depth Uncertainty Estimation via Gaussian Splatting—0
SDGOCC: Semantic and Depth-Guided Bird's-Eye View Transformation for 3D Multimodal Occupancy PredictionCode0
Improved Monocular Depth Prediction Using Distance Transform Over Pre-semantic Contours with Self-supervised Neural Networks—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
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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