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
Beyond Existance: Fulfill 3D Reconstructed Scenes with Pseudo Details—0
BG-Triangle: Bézier Gaussian Triangle for 3D Vectorization and Rendering—0
BG-Triangle: Bezier Gaussian Triangle for 3D Vectorization and Rendering—0
Splatt3R: Zero-shot Gaussian Splatting from Uncalibrated Image Pairs—0
Bile Duct Segmentation Methods Under 3D Slicer Applied to ERCP: Advantages and Disadvantages—0
Binomial Self-Compensation: Mechanism and Suppression of Motion Error in Phase-Shifting Profilometry—0
Bi-objective Framework for Sensor Fusion in RGB-D Multi-View Systems: Applications in Calibration—0
3D Coronary Vessel Reconstruction from Bi-Plane Angiography using Graph Convolutional Networks—0
Biomass phenotyping of oilseed rape through UAV multi-view oblique imaging with 3DGS and SAM model—0
Black-Box Test-Time Shape REFINEment for Single View 3D Reconstruction—0
3D Colored Shape Reconstruction from a Single RGB Image through Diffusion—0
Structure from Motion-based Motion Estimation and 3D Reconstruction of Unknown Shaped Space Debris—0
Blind Face Restoration via Integrating Face Shape and Generative Priors—0
Spurfies: Sparse Surface Reconstruction using Local Geometry Priors—0
Body Knowledge and Uncertainty Modeling for Monocular 3D Human Body Reconstruction—0
SR3D: Unleashing Single-view 3D Reconstruction for Transparent and Specular Object Grasping—0
Bolt3D: Generating 3D Scenes in Seconds—0
An adversarial feature learning based semantic communication method for Human 3D Reconstruction—0
Boosted ab initio Cryo-EM 3D Reconstruction with ACE-EM—0
Boosting Image Super-Resolution Via Fusion of Complementary Information Captured by Multi-Modal Sensors—0
Bootstrap-GS: Self-Supervised Augmentation for High-Fidelity Gaussian Splatting—0
Boundary conditions for Shape from Shading—0
SS3DM: Benchmarking Street-View Surface Reconstruction with a Synthetic 3D Mesh Dataset—0
Branching Gaussian Processes with Applications to Spatiotemporal Reconstruction of 3D Trees—0
Bring Your Rear Cameras for Egocentric 3D Human Pose Estimation—0
Show:102550
← PrevPage 76 of 94Next →
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