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 1076–1100 of 2326 papers

TitleStatusHype
3D-HGS: 3D Half-Gaussian Splatting—0
MaGS: Reconstructing and Simulating Dynamic 3D Objects with Mesh-adsorbed Gaussian Splatting—0
Details Enhancement in Unsigned Distance Field Learning for High-fidelity 3D Surface Reconstruction—0
A Pixel Is Worth More Than One 3D Gaussians in Single-View 3D Reconstruction—0
Learning 3D Robotics Perception using Inductive Priors—0
TetSphere Splatting: Representing High-Quality Geometry with Lagrangian Volumetric Meshes—0
Physically Compatible 3D Object Modeling from a Single Image—0
Neural Radiance Fields for Novel View Synthesis in Monocular Gastroscopy—0
Hierarchical Procedural Framework for Low-latency Robot-Assisted Hand-Object Interaction—0
A Refined 3D Gaussian Representation for High-Quality Dynamic Scene Reconstruction—0
3D Reconstruction with Fast Dipole Sums—0
SDL-MVS: View Space and Depth Deformable Learning Paradigm for Multi-View Stereo Reconstruction in Remote Sensing—0
DINO-SD: Champion Solution for ICRA 2024 RoboDepth Challenge—0
Part123: Part-aware 3D Reconstruction from a Single-view Image—0
Neural Network-Based Tracking and 3D Reconstruction of Baseball Pitch Trajectories from Single-View 2D Video—0
LAM3D: Large Image-Point-Cloud Alignment Model for 3D Reconstruction from Single Image—0
Exploration of Multi-Scale Image Fusion Systems in Intelligent Medical Image Analysis—0
Gaussian Time Machine: A Real-Time Rendering Methodology for Time-Variant Appearances—0
NPLMV-PS: Neural Point-Light Multi-View Photometric Stereo—0
Enhanced 3D Urban Scene Reconstruction and Point Cloud Densification using Gaussian Splatting and Google Earth Imagery—0
CAT3D: Create Anything in 3D with Multi-View Diffusion Models—0
Dynamic NeRF: A Review—0
Hologram: Realtime Holographic Overlays via LiDAR Augmented Reconstruction—0
Comparative Analysis of Advanced Feature Matching Algorithms in Challenging High Spatial Resolution Optical Satellite Stereo Scenarios—0
Gaussian Splatting: 3D Reconstruction and Novel View Synthesis, a Review—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