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 1551–1600 of 2326 papers

TitleStatusHype
MaGS: Reconstructing and Simulating Dynamic 3D Objects with Mesh-adsorbed Gaussian Splatting—0
Reconstructing Animals and the Wild—0
Reconstructing Hand-Object Interactions in the Wild—0
Reconstructing Heterogeneous Biomolecules via Hierarchical Gaussian Mixtures and Part Discovery—0
CryoChains: Heterogeneous Reconstruction of Molecular Assembly of Semi-flexible Chains from Cryo-EM Images—0
Reconstructing In-the-Wild Open-Vocabulary Human-Object Interactions—0
Reconstructing Satellites in 3D from Amateur Telescope Images—0
Using Adaptive Gradient for Texture Learning in Single-View 3D Reconstruction—0
Reconstructing Small 3D Objects in front of a Textured Background—0
Using Orthophoto for Building Boundary Sharpening in the Digital Surface Model—0
Reconstruction-based Pairwise Depth Dataset for Depth Image Enhancement Using CNN—0
Reconstruction of the shape of irregular rough particles from their interferometric images using a convolutional neural network—0
Reconstruct, Rasterize and Backprop: Dense shape and pose estimation from a single image—0
Recovering 3D Planar Arrangements from Videos—0
Recurrent Neural Network for Learning DenseDepth and Ego-Motion from Video—0
3D Instance Segmentation via Multi-Task Metric Learning—0
Refined Equivalent Pinhole Model for Large-scale 3D Reconstruction from Spaceborne CCD Imagery—0
Reflectance and Fluorescent Spectra Recovery based on Fluorescent Chromaticity Invariance under Varying Illumination—0
Refractive COLMAP: Refractive Structure-from-Motion Revisited—0
USTC FLICAR: A Sensors Fusion Dataset of LiDAR-Inertial-Camera for Heavy-duty Autonomous Aerial Work Robots—0
Regist3R: Incremental Registration with Stereo Foundation Model—0
Regularizing disparity estimation via multi task learning with structured light reconstruction—0
Relative Drone-Ground Vehicle Localization using LiDAR and Fisheye Cameras through Direct and Indirect Observations—0
Relative Volume Constraints for Single View 3D Reconstruction—0
3 Dimensional Dense Reconstruction: A Review of Algorithms and Dataset—0
RelMobNet: End-to-end relative camera pose estimation using a robust two-stage training—0
ReLoo: Reconstructing Humans Dressed in Loose Garments from Monocular Video in the Wild—0
3D-HGS: 3D Half-Gaussian Splatting—0
REMIPS: Physically Consistent 3D Reconstruction of Multiple Interacting People under Weak Supervision—0
Rendu basé image avec contraintes sur les gradients—0
UVRM: A Scalable 3D Reconstruction Model from Unposed Videos—0
UW-SDF: Exploiting Hybrid Geometric Priors for Neural SDF Reconstruction from Underwater Multi-view Monocular Images—0
Representation Learning of Point Cloud Upsampling in Global and Local Inputs—0
Representing 3D Shapes with Probabilistic Directed Distance Fields—0
V2V3D: View-to-View Denoised 3D Reconstruction for Light-Field Microscopy—0
Residential Floor Plan Recognition and Reconstruction—0
Resolution-Robust 3D MRI Reconstruction with 2D Diffusion Priors: Diverse-Resolution Training Outperforms Interpolation—0
Resolving Scale Ambiguity Via XSlit Aspect Ratio Analysis—0
V2V3D: View-to-View Denoised 3D Reconstruction for Light Field Microscopy—0
Rethinking Data Input for Point Cloud Upsampling—0
3DGS^2: Near Second-order Converging 3D Gaussian Splatting—0
Rethinking Directional Integration in Neural Radiance Fields—0
Rethinking Road Surface 3D Reconstruction and Pothole Detection: From Perspective Transformation to Disparity Map Segmentation—0
Wireless 3D Point Cloud Delivery Using Deep Graph Neural Networks—0
Revealing the 3D Cosmic Web through Gravitationally Constrained Neural Fields—0
Review of Feed-forward 3D Reconstruction: From DUSt3R to VGGT—0
Revisiting PatchMatch Multi-View Stereo for Urban 3D Reconstruction—0
Revisiting the Role of Texture in 3D Person Re-identification—0
VEIGAR: View-consistent Explicit Inpainting and Geometry Alignment for 3D object Removal—0
RGB2Hands: Real-Time Tracking of 3D Hand Interactions from Monocular RGB Video—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