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 926–950 of 2326 papers

TitleStatusHype
Gromov-Wasserstein Problem with Cyclic Symmetry—0
Contact Area Detector using Cross View Projection Consistency for COVID-19 Projects—0
Anatomical basis of sex differences in the electrocardiogram identified by three-dimensional torso-heart imaging reconstruction pipeline—0
3 Dimensional Dense Reconstruction: A Review of Algorithms and Dataset—0
Generative Multiview Relighting for 3D Reconstruction under Extreme Illumination Variation—0
Consistent sets of lines with no colorful incidence—0
GSIR: Generalizable 3D Shape Interpretation and Reconstruction—0
Generative Densification: Learning to Densify Gaussians for High-Fidelity Generalizable 3D Reconstruction—0
Consistent Recurrent Neural Networks for 3D Neuron Segmentation—0
An Approach for Noise Removal on Depth Images—0
Generating 3D Bio-Printable Patches Using Wound Segmentation and Reconstruction to Treat Diabetic Foot Ulcers—0
Consistent123: Improve Consistency for One Image to 3D Object Synthesis—0
GTR: Improving Large 3D Reconstruction Models through Geometry and Texture Refinement—0
Analytical Derivatives for Differentiable Renderer: 3D Pose Estimation by Silhouette Consistency—0
GURecon: Learning Detailed 3D Geometric Uncertainties for Neural Surface Reconstruction—0
3D Reconstruction through Fusion of Cross-View Images—0
GelSight Wedge: Measuring High-Resolution 3D Contact Geometry with a Compact Robot Finger—0
Consistency Diffusion Models for Single-Image 3D Reconstruction with Priors—0
HaloGS: Loose Coupling of Compact Geometry and Gaussian Splats for 3D Scenes—0
HandS3C: 3D Hand Mesh Reconstruction with State Space Spatial Channel Attention from RGB images—0
GauU-Scene: A Scene Reconstruction Benchmark on Large Scale 3D Reconstruction Dataset Using Gaussian Splatting—0
HDM-Net: Monocular Non-Rigid 3D Reconstruction with Learned Deformation Model—0
HDRGS: High Dynamic Range Gaussian Splatting—0
FIRe: Fast Inverse Rendering using Directional and Signed Distance Functions—0
ConRad: Image Constrained Radiance Fields for 3D Generation from a Single Image—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