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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1876–1900 of 2326 papers

TitleStatusHype
Video Motion Capture from the Part Confidence Maps of Multi-Camera Images by Spatiotemporal Filtering Using the Human Skeletal Model—0
Video Perception Models for 3D Scene Synthesis—0
3D-GMNet: Single-View 3D Shape Recovery as A Gaussian Mixture—0
SADIR: Shape-Aware Diffusion Models for 3D Image Reconstruction—0
SALVE: A 3D Reconstruction Benchmark of Wounds from Consumer-grade Videos—0
View Consistency Aware Holistic Triangulation for 3D Human Pose Estimation—0
SCADE: NeRFs from Space Carving with Ambiguity-Aware Depth Estimates—0
Scalable 3D Reconstruction From Single Particle X-Ray Diffraction Images Based on Online Machine Learning—0
Scalable and High-Quality Neural Implicit Representation for 3D Reconstruction—0
Scale Drift Correction of Camera Geo-Localization using Geo-Tagged Images—0
Embodiment: Self-Supervised Depth Estimation Based on Camera Models—0
View Selection with Geometric Uncertainty Modeling—0
Scene 3-D Reconstruction System in Scattering Medium—0
3D GANs and Latent Space: A comprehensive survey—0
ViiNeuS: Volumetric Initialization for Implicit Neural Surface reconstruction of urban scenes with limited image overlap—0
S&CNet: Monocular Depth Completion for Autonomous Systems and 3D Reconstruction—0
SC-OmniGS: Self-Calibrating Omnidirectional Gaussian Splatting—0
WonderVerse: Extendable 3D Scene Generation with Video Generative Models—0
SCube: Instant Large-Scale Scene Reconstruction using VoxSplats—0
3DFusion, A real-time 3D object reconstruction pipeline based on streamed instance segmented data—0
SDL-MVS: View Space and Depth Deformable Learning Paradigm for Multi-View Stereo Reconstruction in Remote Sensing—0
SD-MVS: Segmentation-Driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization—0
SE(3) Equivariant Convolution and Transformer in Ray Space—0
SE(3) Equivariant Convolution and Transformer in Ray Space—0
Equivariant Light Field Convolution and Transformer—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