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 1651–1700 of 2326 papers

TitleStatusHype
3D Reconstruction from Sketches—0
PBIR-NIE: Glossy Object Capture under Non-Distant Lighting—0
3D Reconstruction from public webcams—0
PC2: Projection-Conditioned Point Cloud Diffusion for Single-Image 3D Reconstruction—0
PCGen: Point Cloud Generator for LiDAR Simulation—0
UniFaceGAN: A Unified Framework for Temporally Consistent Facial Video Editing—0
3D Reconstruction from Full-view Fisheye Camera—0
Unified Few-shot Crack Segmentation and its Precise 3D Automatic Measurement in Concrete Structures—0
3D Reconstruction from Accidental Motion—0
Unified Scene Representation and Reconstruction for 3D Large Language Models—0
When 3D Reconstruction Meets Ubiquitous RGB-D Images—0
Perceiving Unseen 3D Objects by Poking the Objects—0
Efficient NeRF Optimization -- Not All Samples Remain Equally Hard—0
3D Reconstruction by Looking: Instantaneous Blind Spot Detector for Indoor SLAM through Mixed Reality—0
PERF: Performant, Explicit Radiance Fields—0
PerMO: Perceiving More at Once from a Single Image for Autonomous Driving—0
Perspective-consistent multifocus multiview 3D reconstruction of small objects—0
UniSDF: Unifying Neural Representations for High-Fidelity 3D Reconstruction of Complex Scenes with Reflections—0
Perturb-and-Revise: Flexible 3D Editing with Generative Trajectories—0
3D Reconstruction-Based Seed Counting of Sorghum Panicles for Agricultural Inspection—0
PF-LRM: Pose-Free Large Reconstruction Model for Joint Pose and Shape Prediction—0
X-SG^2S: Safe and Generalizable Gaussian Splatting with X-dimensional Watermarks—0
Photogeometric Scene Flow for High-Detail Dynamic 3D Reconstruction—0
Photometric Correction for Infrared Sensors—0
PanicleNeRF: low-cost, high-precision in-field phenotypingof rice panicles with smartphone—0
Photometric Stereo in a Scattering Medium—0
Photometric Stereo in Participating Media Considering Shape-Dependent Forward Scatter—0
Enhanced 3D Urban Scene Reconstruction and Point Cloud Densification using Gaussian Splatting and Google Earth Imagery—0
Photorealistic Monocular 3D Reconstruction of Humans Wearing Clothing—0
PHRIT: Parametric Hand Representation with Implicit Template—0
Unposed Sparse Views Room Layout Reconstruction in the Age of Pretrain Model—0
PhyRecon: Physically Plausible Neural Scene Reconstruction—0
Physically Compatible 3D Object Modeling from a Single Image—0
Physically Plausible 3D Human-Scene Reconstruction from Monocular RGB Image using an Adversarial Learning Approach—0
Unsupervised 3D Reconstruction from a Single Image via Adversarial Learning—0
Physics-informed neural networks for gravity currents reconstruction from limited data—0
Piecewise-Planar 3D Approximation From Wide-Baseline Stereo—0
PiMPeR: Piecewise Dense 3D Reconstruction from Multi-View and Multi-Illumination Images—0
Pipeline for 3D reconstruction of the human body from AR/VR headset mounted egocentric cameras—0
Unsupervised 3D Reconstruction Networks—0
Pixel3DMM: Versatile Screen-Space Priors for Single-Image 3D Face Reconstruction—0
Pixel-Aligned Multi-View Generation with Depth Guided Decoder—0
3D Reconstruction and Alignment by Consumer RGB-D Sensors and Fiducial Planar Markers for Patient Positioning in Radiation Therapy—0
3DRealCar: An In-the-wild RGB-D Car Dataset with 360-degree Views—0
Pixel-variant Local Homography for Fisheye Stereo Rectification Minimizing Resampling Distortion—0
PL_1P -- Point-line Minimal Problems under Partial Visibility in Three Views—0
PL₁P - Point-line Minimal Problems under Partial Visibility in Three Views—0
Plane-Based Optimization of Geometry and Texture for RGB-D Reconstruction of Indoor Scenes—0
What Do Single-view 3D Reconstruction Networks Learn?—0
Unsupervised Multi-Person 3D Human Pose Estimation From 2D Poses Alone—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