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 1151–1175 of 2326 papers

TitleStatusHype
3DRIMR: 3D Reconstruction and Imaging via mmWave Radar based on Deep Learning—0
Towards Pointless Structure From Motion: 3D Reconstruction and Camera Parameters From General 3D Curves—0
Mesh deformation-based single-view 3D reconstruction of thin eyeglasses frames with differentiable rendering—0
MeshFormer: High-Quality Mesh Generation with 3D-Guided Reconstruction Model—0
Towards the Probabilistic Fusion of Learned Priors into Standard Pipelines for 3D Reconstruction—0
Single-View 3D Object Reconstruction from Shape Priors in Memory—0
MetaFood3D: 3D Food Dataset with Nutrition Values—0
MetaFood CVPR 2024 Challenge on Physically Informed 3D Food Reconstruction: Methods and Results—0
Aberration Correcting Vision Transformers for High-Fidelity Metalens Imaging—0
Method for the generation of depth images for view-based shape retrieval of 3D CAD model from partial point cloud—0
Methodology to analyze the accuracy of 3D objects reconstructed with collaborative robot based monocular LSD-SLAM—0
MeTTA: Single-View to 3D Textured Mesh Reconstruction with Test-Time Adaptation—0
MFP3D: Monocular Food Portion Estimation Leveraging 3D Point Clouds—0
MGSO: Monocular Real-time Photometric SLAM with Efficient 3D Gaussian Splatting—0
Calculating Pose with Vanishing Points of Visual-Sphere Perspective Model—0
3D Reconstruction with Low Resolution, Small Baseline and High Radial Distortion Stereo Images—0
Micro-macro Wavelet-based Gaussian Splatting for 3D Reconstruction from Unconstrained Images—0
Towards ultra-high resolution 3D reconstruction of a whole rat brain from 3D-PLI data—0
DirectPET: Full Size Neural Network PET Reconstruction from Sinogram Data—0
MITI: SLAM Benchmark for Laparoscopic Surgery—0
Mixing-Denoising Generalizable Occupancy Networks—0
Mixture of neural fields for heterogeneous reconstruction in cryo-EM—0
Multi-View Large Reconstruction Model via Geometry-Aware Positional Encoding and Attention—0
MobiFuse: A High-Precision On-device Depth Perception System with Multi-Data Fusion—0
Mobile3DRecon: Real-time Monocular 3D Reconstruction on a Mobile Phone—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