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 1351–1375 of 2326 papers

TitleStatusHype
Obj-NeRF: Extract Object NeRFs from Multi-view Images—0
Occam's LGS: A Simple Approach for Language Gaussian Splatting—0
X-Section: Cross-Section Prediction for Enhanced RGBD Fusion—0
3D Reconstruction of Heterogeneous Virus Particles with Statistical Geometric Symmetry—0
Occupancy Flow: 4D Reconstruction by Learning Particle Dynamics—0
What You Can Reconstruct From a Shadow—0
3D Reconstruction of Deformable Revolving Object under Heavy Hand Interaction—0
ODHSR: Online Dense 3D Reconstruction of Humans and Scenes from Monocular Videos—0
UMono: Physical Model Informed Hybrid CNN-Transformer Framework for Underwater Monocular Depth Estimation—0
3D Reconstruction of Curvilinear Structures with Stereo Matching DeepConvolutional Neural Networks—0
OmniIndoor3D: Comprehensive Indoor 3D Reconstruction—0
OmniNeRF: Hybriding Omnidirectional Distance and Radiance fields for Neural Surface Reconstruction—0
Unbiased 4D: Monocular 4D Reconstruction with a Neural Deformation Model—0
3D Reconstruction of Crime Scenes and Design Considerations for an Interactive Investigation Tool—0
Unbiased Photometric Stereo for Colored Surfaces: A Variational Approach—0
One Ring to Rule Them All: a simple solution to multi-view 3D-Reconstruction of shapes with unknown BRDF via a small Recurrent ResNet—0
X-Section: Cross-Section Prediction for Enhanced RGB-D Fusion—0
ONIX: an X-ray deep-learning tool for 3D reconstructions from sparse views—0
Uncertainty-Aware Diffusion Guided Refinement of 3D Scenes—0
Online Adaptation for Consistent Mesh Reconstruction in the Wild—0
Uncertainty-Aware Human Mesh Recovery From Video by Learning Part-Based 3D Dynamics—0
On Monocular Depth Estimation and Uncertainty Quantification using Classification Approaches for Regression—0
3D Reconstruction of Clothes using a Human Body Model and its Application to Image-based Virtual Try-On—0
On the Detection of Mutual Influences and Their Consideration in Reinforcement Learning Processes—0
On the Diagnostic of Road Pathway Visibility—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