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 1001–1050 of 2326 papers

TitleStatusHype
Energy Based Multi-model Fitting & Matching for 3D Reconstruction—0
BRUM: Robust 3D Vehicle Reconstruction from 360 Sparse Images—0
Deep Event Stereo Leveraged by Event-to-Image Translation—0
IM360: Textured Mesh Reconstruction for Large-scale Indoor Mapping with 360^ Cameras—0
Addressing the Shape-Radiance Ambiguity in View-Dependent Radiance Fields—0
IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation—0
End-to-End Multi-View Structure-from-Motion with Hypercorrelation Volumes—0
Image-based underwater 3D reconstruction for Cultural Heritage: from image collection to 3D. Critical steps and considerations—0
End-to-End Latency Optimization of Multi-view 3D Reconstruction for Disaster Response—0
Image compression optimized for 3D reconstruction by utilizing deep neural networks—0
Image Reconstruction for Accelerated MR Scan with Faster Fourier Convolutional Neural Networks—0
Deep Learned Full-3D Object Completion from Single View—0
Image-to-Voxel Model Translation for 3D Scene Reconstruction and Segmentation—0
Bring Your Rear Cameras for Egocentric 3D Human Pose Estimation—0
End-To-End Convolutional Neural Network for 3D Reconstruction of Knee Bones From Bi-Planar X-Ray Images—0
End-to-end 3D shape inverse rendering of different classes of objects from a single input image—0
Branching Gaussian Processes with Applications to Spatiotemporal Reconstruction of 3D Trees—0
3D Reconstruction of Curvilinear Structures with Stereo Matching DeepConvolutional Neural Networks—0
Improved Descriptors for Patch Matching and Reconstruction—0
Improving 3D Finger Traits Recognition via Generalizable Neural Rendering—0
CryoSPIN: Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference—0
Deep Learning-Based Direct Leaf Area Estimation using Two RGBD Datasets for Model Development—0
Ladybird: Quasi-Monte Carlo Sampling for Deep Implicit Field Based 3D Reconstruction with Symmetry—0
Laparoscopic Scene Analysis for Intraoperative Visualisation of Gamma Probe Signals in Minimally Invasive Cancer Surgery—0
Large-Scale, Metric Structure From Motion for Unordered Light Fields—0
EndoSparse: Real-Time Sparse View Synthesis of Endoscopic Scenes using Gaussian Splatting—0
Endoscopy artifact detection (EAD 2019) challenge dataset—0
EndoMetric: Near-Light Monocular Metric Scale Estimation in Endoscopy—0
EndoGaussians: Single View Dynamic Gaussian Splatting for Deformable Endoscopic Tissues Reconstruction—0
Boundary conditions for Shape from Shading—0
Adaptive View Planning for Aerial 3D Reconstruction—0
EndoFlow-SLAM: Real-Time Endoscopic SLAM with Flow-Constrained Gaussian Splatting—0
Multi-tiling Neural Radiance Field (NeRF) -- Geometric Assessment on Large-scale Aerial Datasets—0
Bootstrap-GS: Self-Supervised Augmentation for High-Fidelity Gaussian Splatting—0
EM-based approach to 3D reconstruction from single-waveform multispectral Lidar data—0
Boosting Image Super-Resolution Via Fusion of Complementary Information Captured by Multi-Modal Sensors—0
Adaptive Surface Reconstruction With Multiscale Convolutional Kernels—0
3D Reconstruction of Crime Scenes and Design Considerations for an Interactive Investigation Tool—0
Elite360D: Towards Efficient 360 Depth Estimation via Semantic- and Distance-Aware Bi-Projection Fusion—0
Elevation Estimation-Driven Building 3D Reconstruction from Single-View Remote Sensing Imagery—0
Boosted ab initio Cryo-EM 3D Reconstruction with ACE-EM—0
EGP3D: Edge-guided Geometric Preserving 3D Point Cloud Super-resolution for RGB-D camera—0
Adaptive Joint Optimization for 3D Reconstruction with Differentiable Rendering—0
Ego3DT: Tracking Every 3D Object in Ego-centric Videos—0
EGGS: Edge Guided Gaussian Splatting for Radiance Fields—0
Bolt3D: Generating 3D Scenes in Seconds—0
Efficient View Clustering and Selection for City-Scale 3D Reconstruction—0
AdaOcc: Adaptive-Resolution Occupancy Prediction—0
3D Reconstruction of Clothes using a Human Body Model and its Application to Image-based Virtual Try-On—0
3D Freehand Ultrasound using Visual Inertial and Deep Inertial Odometry for Measuring Patellar Tracking—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