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 1176–1200 of 2326 papers

TitleStatusHype
DiffPoint: Single and Multi-view Point Cloud Reconstruction with ViT Based Diffusion Model—0
Dense Matchers for Dense Tracking—0
Evaluating Neural Radiance Fields (NeRFs) for 3D Plant Geometry Reconstruction in Field Conditions—0
IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation—0
Neural Rendering based Urban Scene Reconstruction for Autonomous Driving—0
MoD-SLAM: Monocular Dense Mapping for Unbounded 3D Scene Reconstruction—0
Denoising Diffusion via Image-Based Rendering—0
Diffusion-based Light Field Synthesis—0
DARCS: Memory-Efficient Deep Compressed Sensing Reconstruction for Acceleration of 3D Whole-Heart Coronary MR Angiography—0
Enhanced fringe-to-phase framework using deep learning—0
Domain adaptation strategies for 3D reconstruction of the lumbar spine using real fluoroscopy data—0
2L3: Lifting Imperfect Generated 2D Images into Accurate 3D—0
Multi-Person 3D Pose Estimation from Multi-View Uncalibrated Depth Cameras—0
GauU-Scene: A Scene Reconstruction Benchmark on Large Scale 3D Reconstruction Dataset Using Gaussian Splatting—0
TIFu: Tri-directional Implicit Function for High-Fidelity 3D Character Reconstruction—0
EndoGaussians: Single View Dynamic Gaussian Splatting for Deformable Endoscopic Tissues Reconstruction—0
IRIS: Inverse Rendering of Indoor Scenes from Low Dynamic Range Images—0
The State of Computer Vision Research in AfricaCode0
Dense 3D Reconstruction Through Lidar: A Comparative Study on Ex-vivo Porcine Tissue—0
SD-MVS: Segmentation-Driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization—0
3D Reconstruction of Interacting Multi-Person in Clothing from a Single Image—0
AGG: Amortized Generative 3D Gaussians for Single Image to 3D—0
RHOBIN Challenge: Reconstruction of Human Object Interaction—0
Neural Rendering and Its Hardware Acceleration: A Review—0
Noise-NeRF: Hide Information in Neural Radiance Fields using Trainable Noise—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