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 1001–1025 of 2326 papers

TitleStatusHype
DeRainGS: Gaussian Splatting for Enhanced Scene Reconstruction in Rainy Environments—0
SpaRP: Fast 3D Object Reconstruction and Pose Estimation from Sparse Views—0
MeshFormer: High-Quality Mesh Generation with 3D-Guided Reconstruction Model—0
P3P: Pseudo-3D Pre-training for Scaling 3D Voxel-based Masked AutoencodersCode0
Single-image coherent reconstruction of objects and humans—0
Rethinking the Key Factors for the Generalization of Remote Sensing Stereo Matching NetworksCode0
HDRGS: High Dynamic Range Gaussian Splatting—0
NeRF-US: Removing Ultrasound Imaging Artifacts from Neural Radiance Fields in the Wild—0
PBIR-NIE: Glossy Object Capture under Non-Distant Lighting—0
3D Reconstruction of Protein Structures from Multi-view AFM Images using Neural Radiance Fields (NeRFs)—0
Visual SLAM with 3D Gaussian Primitives and Depth Priors Enabling Novel View Synthesis—0
Mesh deformation-based single-view 3D reconstruction of thin eyeglasses frames with differentiable rendering—0
AugGS: Self-augmented Gaussians with Structural Masks for Sparse-view 3D Reconstruction—0
Efficient NeRF Optimization -- Not All Samples Remain Equally Hard—0
PanicleNeRF: low-cost, high-precision in-field phenotypingof rice panicles with smartphone—0
Structure from Motion-based Motion Estimation and 3D Reconstruction of Unknown Shaped Space Debris—0
Embodiment: Self-Supervised Depth Estimation Based on Camera Models—0
Enhanced Knee Kinematics: Leveraging Deep Learning and Morphing Algorithms for 3D Implant Modeling—0
IG-SLAM: Instant Gaussian SLAM—0
UlRe-NeRF: 3D Ultrasound Imaging through Neural Rendering with Ultrasound Reflection Direction Parameterization—0
X-ray nano-holotomography reconstruction with simultaneous probe retrieval—0
SALVE: A 3D Reconstruction Benchmark of Wounds from Consumer-grade Videos—0
Cycle3D: High-quality and Consistent Image-to-3D Generation via Generation-Reconstruction Cycle—0
A Bayesian Approach Toward Robust Multidimensional Ellipsoid-Specific FittingCode0
Floating No More: Object-Ground Reconstruction 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