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 1976–2000 of 2326 papers

TitleStatusHype
Single-View View Synthesis with Self-Rectified Pseudo-Stereo—0
SIR-DIFF: Sparse Image Sets Restoration with Multi-View Diffusion Model—0
3D Face Reconstruction From Radar Images—0
Skeleton Driven Non-rigid Motion Tracking and 3D Reconstruction—0
Sketch2CADScript: 3D Scene Reconstruction from 2D Sketch using Visual Transformer and Rhino Grasshopper—0
Enhanced Knee Kinematics: Leveraging Deep Learning and Morphing Algorithms for 3D Implant Modeling—0
3DeepCT: Learning Volumetric Scattering Tomography of Clouds—0
Slice3D: Multi-Slice, Occlusion-Revealing, Single View 3D Reconstruction—0
Slice3D: Multi-Slice Occlusion-Revealing Single View 3D Reconstruction—0
Small Drone Field Experiment: Data Collection & Processing—0
SmartPortraits: Depth Powered Handheld Smartphone Dataset of Human Portraits for State Estimation, Reconstruction and Synthesis—0
Visual Odometry with an Event Camera Using Continuous Ray Warping and Volumetric Contrast Maximization—0
smFISH_batchRun: A smFISH image processing tool for single-molecule RNA Detection and 3D reconstruction—0
Visual SLAM with 3D Gaussian Primitives and Depth Priors Enabling Novel View Synthesis—0
SMPL Normal Map Is All You Need for Single-view Textured Human Reconstruction—0
SNeRL: Semantic-aware Neural Radiance Fields for Reinforcement Learning—0
SNeS: Learning Probably Symmetric Neural Surfaces from Incomplete Data—0
SobolevFusion: 3D Reconstruction of Scenes Undergoing Free Non-Rigid Motion—0
Soccer on Your Tabletop—0
Social Behavior Prediction from First Person Videos—0
Solving Uncalibrated Photometric Stereo Using Fewer Images by Jointly Optimizing Low-rank Matrix Completion and Integrability—0
SonarSplat: Novel View Synthesis of Imaging Sonar via Gaussian Splatting—0
Sora Generates Videos with Stunning Geometrical Consistency—0
IG-SLAM: Instant Gaussian SLAM—0
Sparc3D: Sparse Representation and Construction for High-Resolution 3D Shapes Modeling—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