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 1226–1250 of 2326 papers

TitleStatusHype
In-Hand 3D Object Reconstruction from a Monocular RGB Video—0
Input-level Inductive Biases for 3D Reconstruction—0
Accurate Deep Direct Geo-Localization from Ground Imagery and Phone-Grade GPS—0
Accurate 3D Reconstruction of Dynamic Scenes from Monocular Image Sequences with Severe Occlusions—0
Instrument-Splatting: Controllable Photorealistic Reconstruction of Surgical Instruments Using Gaussian Splatting—0
Integration of the 3D Environment for UAV Onboard Visual Object Tracking—0
Integration of Absolute Orientation Measurements in the KinectFusion Reconstruction pipeline—0
Intensity Video Guided 4D Fusion for Improved Highly Dynamic 3D Reconstruction—0
Interaction-Driven Active 3D Reconstruction with Object Interiors—0
Interactive Manipulation and Visualization of 3D Brain MRI for Surgical Training—0
A Brief Survey of Image Processing Algorithms in Electrical Capacitance Tomography—0
In-the-Wild Single Camera 3D Reconstruction Through Moving Water Surfaces—0
Invariant-based Mapping of Space During General Motion of an Observer—0
Investigating Spherical Epipolar Rectification for Multi-View Stereo 3D Reconstruction—0
INV-Flow2PoseNet: Light-Resistant Rigid Object Pose from Optical Flow of RGB-D Images using Images, Normals and Vertices—0
IOVS4NeRF:Incremental Optimal View Selection for Large-Scale NeRFs—0
IRIS: Inverse Rendering of Indoor Scenes from Low Dynamic Range Images—0
IsMo-GAN: Adversarial Learning for Monocular Non-Rigid 3D Reconstruction—0
Isometric Multi-Shape Matching—0
Isotropic Gaussian Splatting for Real-Time Radiance Field Rendering—0
Is Single-View Mesh Reconstruction Ready for Robotics?—0
Iterative Clustering with Game-Theoretic Matching for Robust Multi-consistency Correspondence—0
Weakly-Supervised 3D Pose Estimation from a Single Image using Multi-View Consistency—0
IXGS-Intraoperative 3D Reconstruction from Sparse, Arbitrarily Posed Real X-rays—0
Joint 3D Reconstruction of a Static Scene and Moving Objects—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