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

Showing 18011825 of 2326 papers

TitleStatusHype
Unpaired Motion Style Transfer from Video to AnimationCode2
HDD-Net: Hybrid Detector Descriptor with Mutual Interactive LearningCode1
FroDO: From Detections to 3D Objects0
A Simple and Scalable Shape Representation for 3D Reconstruction0
Multi-view data capture using edge-synchronised mobiles0
Stomach 3D Reconstruction Based on Virtual Chromoendoscopic Image Generation0
Reconstruct, Rasterize and Backprop: Dense shape and pose estimation from a single image0
Through the Looking Glass: Neural 3D Reconstruction of Transparent ShapesCode1
The Covering-Assignment Problem for Swarm-powered Ad-hoc Clouds: A Distributed 3D Mapping Use-caseCode0
Robust 3D reconstruction of dynamic scenes from single-photon lidar using Beta-divergences0
Calculating Pose with Vanishing Points of Visual-Sphere Perspective Model0
Few-Shot Single-View 3-D Object Reconstruction with Compositional PriorsCode1
ARCH: Animatable Reconstruction of Clothed HumansCode0
Differential 3D Facial Recognition: Adding 3D to Your State-of-the-Art 2D Method0
Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB ImageCode1
Occlusion-Aware Depth Estimation with Adaptive Normal ConstraintsCode1
End-To-End Convolutional Neural Network for 3D Reconstruction of Knee Bones From Bi-Planar X-Ray Images0
Image compression optimized for 3D reconstruction by utilizing deep neural networks0
Learning Implicit Surface Light FieldsCode2
High-Accuracy Facial Depth Models derived from 3D Synthetic Data0
Weakly-supervised 3D coronary artery reconstruction from two-view angiographic images0
Deep Local Shapes: Learning Local SDF Priors for Detailed 3D ReconstructionCode1
Atlas: End-to-End 3D Scene Reconstruction from Posed ImagesCode2
ASLFeat: Learning Local Features of Accurate Shape and LocalizationCode1
Multiview Neural Surface Reconstruction by Disentangling Geometry and AppearanceCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
13D-R2N2Overall0.63Unverified
2GipumaOverall0.58Unverified
3COLMAPOverall0.53Unverified
4MVSNetOverall0.46Unverified
5Vis-MVSNetOverall0.37Unverified
6AA-RMVSNetOverall0.36Unverified
7Cas-MVSNetOverall0.36Unverified
8EPP-MVSNetOverall0.36Unverified
9PatchmatchNetOverall0.35Unverified
10CVP-MVSNetOverall0.35Unverified
#ModelMetricClaimedVerifiedStatus
1MD-GONIoU92.8Unverified
2POCOIoU92.6Unverified
3FS-SDFIoU91.2Unverified
4DP-ConvONetIoU89.5Unverified
5ConvONetIoU88.4Unverified
6ONetIoU76.1Unverified
7EVolTIoU73.8Unverified
8ZubicLioIoU65.43Unverified
#ModelMetricClaimedVerifiedStatus
1AttSets3DIoU0.64Unverified
2PSGN3DIoU0.64Unverified
3OGN3DIoU0.6Unverified
43D-R2N23DIoU0.56Unverified
#ModelMetricClaimedVerifiedStatus
1Scan2CADAverage Accuracy31.68Unverified
23DMatchAverage Accuracy10.29Unverified
#ModelMetricClaimedVerifiedStatus
1SVCPChamfer10Unverified
#ModelMetricClaimedVerifiedStatus
1EVLAccuracy18.2Unverified
#ModelMetricClaimedVerifiedStatus
1EVLAccuracy5.7Unverified
#ModelMetricClaimedVerifiedStatus
1Atlas (finetuned)3DIoU89.4Unverified