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 1851–1900 of 2326 papers

TitleStatusHype
Image compression optimized for 3D reconstruction by utilizing deep neural networks—0
High-Accuracy Facial Depth Models derived from 3D Synthetic Data—0
Weakly-supervised 3D coronary artery reconstruction from two-view angiographic images—0
Graph Attention Network based Pruning for Reconstructing 3D Liver Vessel Morphology from Contrasted CT Images—0
Oral-3D: Reconstructing the 3D Bone Structure of Oral Cavity from 2D Panoramic X-ray—0
Uncertainty depth estimation with gated images for 3D reconstruction—0
PL_1P -- Point-line Minimal Problems under Partial Visibility in Three Views—0
Single-View 3D Object Reconstruction from Shape Priors in Memory—0
STD-Net: Structure-preserving and Topology-adaptive Deformation Network for 3D Reconstruction from a Single Image—0
Fast and Regularized Reconstruction of Building Façades from Street-View Images using Binary Integer ProgrammingCode0
Globally optimal point set registration by joint symmetry plane fitting—0
Deep Learning in Medical Ultrasound Image Segmentation: a Review—0
HRINet: Alternative Supervision Network for High-resolution CT image Interpolation—0
Self-Supervised Object-in-Gripper Segmentation from Robotic Motions—0
Deep NRSfM++: Towards Unsupervised 2D-3D Lifting in the WildCode0
Synergetic Reconstruction from 2D Pose and 3D Motion for Wide-Space Multi-Person Video Motion Capture in the WildCode0
A Two-step Calibration Method for Unfocused Light Field Camera Based on Projection Model Analysis—0
Learning 3D Human Shape and Pose from Dense Body PartsCode0
Graph-Based Parallel Large Scale Structure from MotionCode0
Learning to Generate Dense Point Clouds with Textures on Multiple CategoriesCode0
Cost Volume Pyramid Based Depth Inference for Multi-View StereoCode0
Surface HOF: Surface Reconstruction from a Single Image Using Higher Order Function Networks—0
Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D SupervisionCode0
SDFDiff: Differentiable Rendering of Signed Distance Fields for 3D Shape OptimizationCode0
C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds—0
One Framework to Register Them All: PointNet Encoding for Point Cloud AlignmentCode0
EM-based approach to 3D reconstruction from single-waveform multispectral Lidar data—0
3D-GMNet: Single-View 3D Shape Recovery as A Gaussian Mixture—0
Video Motion Capture from the Part Confidence Maps of Multi-Camera Images by Spatiotemporal Filtering Using the Human Skeletal Model—0
Bundle Adjustment Revisited—0
Pyramid Multi-view Stereo Net with Self-adaptive View AggregationCode0
Perspective-consistent multifocus multiview 3D reconstruction of small objects—0
FlowNet3D++: Geometric Losses For Deep Scene Flow Estimation—0
Fixing Implicit Derivatives: Trust-Region Based Learning of Continuous Energy FunctionsCode0
Bat-G net: Bat-inspired High-Resolution 3D Image Reconstruction using Ultrasonic Echoes—0
DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction—0
Domes to Drones: Self-Supervised Active Triangulation for 3D Human Pose ReconstructionCode0
PU-GCN: Point Cloud Upsampling using Graph Convolutional NetworksCode0
SG-NN: Sparse Generative Neural Networks for Self-Supervised Scene Completion of RGB-D ScansCode0
Deep Stereo using Adaptive Thin Volume Representation with Uncertainty AwarenessCode0
PQ-NET: A Generative Part Seq2Seq Network for 3D ShapesCode0
Discriminative training of conditional random fields with probably submodular constraints—0
Deep-Learning Assisted High-Resolution Binocular Stereo Depth Reconstruction—0
DR-KFS: A Differentiable Visual Similarity Metric for 3D Shape Reconstruction—0
Superpixel Soup: Monocular Dense 3D Reconstruction of a Complex Dynamic Scene—0
Tigris: Architecture and Algorithms for 3D Perception in Point CloudsCode0
GraphX-Convolution for Point Cloud Deformation in 2D-to-3D ConversionCode0
Dense 3D Reconstruction for Visual Tunnel Inspection using Unmanned Aerial Vehicle—0
Technical Report: Co-learning of geometry and semantics for online 3D mapping—0
Probabilistic Inference for Camera Calibration in Light Microscopy under Circular MotionCode0
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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