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 1051–1075 of 2326 papers

TitleStatusHype
ACT-R: Adaptive Camera Trajectories for Single View 3D Reconstruction—0
Efficient Online Surface Correction for Real-time Large-Scale 3D Reconstruction—0
3D Reconstruction in the Presence of Glasses by Acoustic and Stereo Fusion—0
Efficient moving point handling for incremental 3D manifold reconstruction—0
Blind Face Restoration via Integrating Face Shape and Generative Priors—0
Semihierarchical Reconstruction and Weak-area Revisiting for Robotic Visual Seafloor Mapping—0
Efficient Inference of Continuous Markov Random Fields with Polynomial Potentials—0
ActiveRMAP: Radiance Field for Active Mapping And Planning—0
360Recon: An Accurate Reconstruction Method Based on Depth Fusion from 360 Images—0
Efficient Image-Space Extraction and Representation of 3D Surface Topography—0
Efficient Global Optimization of Non-differentiable, Symmetric Objectives for Multi Camera Placement—0
Efficient and Robust Training of Dense Object Nets for Multi-Object Robot Manipulation—0
Black-Box Test-Time Shape REFINEment for Single View 3D Reconstruction—0
Active Neural 3D Reconstruction with Colorized Surface Voxel-based View Selection—0
Efficient 3D Room Shape Recovery From a Single Panorama—0
Efficient 3D Reconstruction, Streaming and Visualization of Static and Dynamic Scene Parts for Multi-client Live-telepresence in Large-scale Environments—0
Effective Rank Analysis and Regularization for Enhanced 3D Gaussian Splatting—0
Edge Projection-Based Adaptive View Selection for Cone-Beam CT—0
Biomass phenotyping of oilseed rape through UAV multi-view oblique imaging with 3DGS and SAM model—0
3D Reconstruction in Noisy Agricultural Environments: A Bayesian Optimization Perspective for View Planning—0
2L3: Lifting Imperfect Generated 2D Images into Accurate 3D—0
Edge-preserving Near-light Photometric Stereo with Neural Surfaces—0
Edge Preserving Implicit Surface Representation of Point Clouds—0
Bi-objective Framework for Sensor Fusion in RGB-D Multi-View Systems: Applications in Calibration—0
Echo-Reconstruction: Audio-Augmented 3D Scene 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