SOTAVerified

3D Reconstruction

3D Reconstruction is the task of creating a 3D model or representation of an object or scene from 2D images or other data sources. The goal of 3D reconstruction is to create a virtual representation of an object or scene that can be used for a variety of purposes, such as visualization, animation, simulation, and analysis. It can be used in fields such as computer vision, robotics, and virtual reality.

Image: Gwak et al

Papers

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Showing 301–325 of 2326 papers

TitleStatusHype
WeatherGS: 3D Scene Reconstruction in Adverse Weather Conditions via Gaussian SplattingCode2
PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models—0
Resolution-Robust 3D MRI Reconstruction with 2D Diffusion Priors: Diverse-Resolution Training Outperforms Interpolation—0
LUCES-MV: A Multi-View Dataset for Near-Field Point Light Source Photometric Stereo—0
Context-Aware Outlier Rejection for Robust Multi-View 3D Tracking of Similar Small Birds in An Outdoor AviaryCode0
EasyVis2: A Real Time Multi-view 3D Visualization for Laparoscopic Surgery Training Enhanced by a Deep Neural Network YOLOv8-Pose—0
An Immersive Multi-Elevation Multi-Seasonal Dataset for 3D Reconstruction and Visualization—0
Improving Geometry in Sparse-View 3DGS via Reprojection-based DoF Separation—0
GURecon: Learning Detailed 3D Geometric Uncertainties for Neural Surface Reconstruction—0
Diffusion priors for Bayesian 3D reconstruction from incomplete measurements—0
GenHMR: Generative Human Mesh Recovery—0
Generative Multiview Relighting for 3D Reconstruction under Extreme Illumination Variation—0
GSRender: Deduplicated Occupancy Prediction via Weakly Supervised 3D Gaussian Splatting—0
MegaSynth: Scaling Up 3D Scene Reconstruction with Synthesized Data—0
Prompting Depth Anything for 4K Resolution Accurate Metric Depth EstimationCode5
MobiFuse: A High-Precision On-device Depth Perception System with Multi-Data Fusion—0
Turbo-GS: Accelerating 3D Gaussian Fitting for High-Quality Radiance Fields—0
SemStereo: Semantic-Constrained Stereo Matching Network for Remote Sensing—0
MASt3R-SLAM: Real-Time Dense SLAM with 3D Reconstruction PriorsCode7
PanSplat: 4K Panorama Synthesis with Feed-Forward Gaussian SplattingCode3
View Transformation Robustness for Multi-View 3D Object Reconstruction with Reconstruction Error-Guided View SelectionCode0
EGP3D: Edge-guided Geometric Preserving 3D Point Cloud Super-resolution for RGB-D camera—0
Wonderland: Navigating 3D Scenes from a Single Image—0
3D^2-Actor: Learning Pose-Conditioned 3D-Aware Denoiser for Realistic Gaussian Avatar ModelingCode1
IDArb: Intrinsic Decomposition for Arbitrary Number of Input Views and Illuminations—0
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All datasetsDTUShapeNetData3D−R2N2Scan2CAD3DPeopleAria Digital Twin DatasetAria Synthetic EnvironmentsScanNet

Benchmark Results

#ModelMetricClaimedVerifiedStatus
13D-R2N2Overall0.63—Unverified
2GipumaOverall0.58—Unverified
3COLMAPOverall0.53—Unverified
4MVSNetOverall0.46—Unverified
5Vis-MVSNetOverall0.37—Unverified
6AA-RMVSNetOverall0.36—Unverified
7Cas-MVSNetOverall0.36—Unverified
8EPP-MVSNetOverall0.36—Unverified
9PatchmatchNetOverall0.35—Unverified
10CVP-MVSNetOverall0.35—Unverified
#ModelMetricClaimedVerifiedStatus
1MD-GONIoU92.8—Unverified
2POCOIoU92.6—Unverified
3FS-SDFIoU91.2—Unverified
4DP-ConvONetIoU89.5—Unverified
5ConvONetIoU88.4—Unverified
6ONetIoU76.1—Unverified
7EVolTIoU73.8—Unverified
8ZubicLioIoU65.43—Unverified
#ModelMetricClaimedVerifiedStatus
1AttSets3DIoU0.64—Unverified
2PSGN3DIoU0.64—Unverified
3OGN3DIoU0.6—Unverified
43D-R2N23DIoU0.56—Unverified
#ModelMetricClaimedVerifiedStatus
1Scan2CADAverage Accuracy31.68—Unverified
23DMatchAverage Accuracy10.29—Unverified
#ModelMetricClaimedVerifiedStatus
1SVCPChamfer10—Unverified
#ModelMetricClaimedVerifiedStatus
1EVLAccuracy18.2—Unverified
#ModelMetricClaimedVerifiedStatus
1EVLAccuracy5.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Atlas (finetuned)3DIoU89.4—Unverified