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 1376–1400 of 2326 papers

TitleStatusHype
3D Shape Reconstruction from a Single 2D Image via 2D-3D Self-Consistency—0
3D Segmentation of Neuronal Nuclei and Cell-Type Identification using Multi-channel Information—0
3D Scene Creation and Rendering via Rough Meshes: A Lighting Transfer Avenue—0
Machine Learning for Detection of 3D Features using sparse X-ray data—0
Machine Vision System for 3D Plant Phenotyping—0
MAGE : Single Image to Material-Aware 3D via the Multi-View G-Buffer Estimation Model—0
Mapillary Street-Level Sequences: A Dataset for Lifelong Place Recognition—0
MAP Visibility Estimation for Large-Scale Dynamic 3D Reconstruction—0
Towards Learning Neural Representations from Shadows—0
Towards Live 3D Reconstruction from Wearable Video: An Evaluation of V-SLAM, NeRF, and Videogrammetry Techniques—0
MarrNet: 3D Shape Reconstruction via 2.5D Sketches—0
3D Scattering Tomography by Deep Learning with Architecture Tailored to Cloud Fields—0
Matching-based Depth Camera and Mirrors for 3D Reconstruction—0
Towards Mobile Sensing with Event Cameras on High-agility Resource-constrained Devices: A Survey—0
"Maximizing rigidity" revisited: a convex programming approach for generic 3D shape reconstruction from multiple perspective views—0
Towards Non-contact 3D Ultrasound for Wrist Imaging—0
Towards Panoptic 3D Parsing for Single Image in the Wild—0
MD-Net: Multi-Detector for Local Feature Extraction—0
3D Scanning System for Automatic High-Resolution Plant Phenotyping—0
MegaSynth: Scaling Up 3D Scene Reconstruction with Synthesized Data—0
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
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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