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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1301–1350 of 2326 papers

TitleStatusHype
Uncertainty Guided Policy for Active Robotic 3D Reconstruction using Neural Radiance Fields—0
Neural Implicit Surface Reconstruction using Imaging Sonar—0
End-to-End Multi-View Structure-from-Motion with Hypercorrelation Volumes—0
INV-Flow2PoseNet: Light-Resistant Rigid Object Pose from Optical Flow of RGB-D Images using Images, Normals and Vertices—0
Articulated 3D Human-Object Interactions from RGB Videos: An Empirical Analysis of Approaches and ChallengesCode1
Multi-NeuS: 3D Head Portraits from Single Image with Neural Implicit Functions—0
3D Single-pixel imaging with active sampling patterns and learning based reconstruction—0
Deep Learning Assisted Optimization for 3D Reconstruction from Single 2D Line Drawings—0
A comprehensive survey on recent deep learning-based methods applied to surgical data—0
SimpleRecon: 3D Reconstruction Without 3D ConvolutionsCode3
Inferring Implicit 3D Representations from Human Figures on Pictorial Maps—0
Fast Auto-Differentiable Digitally Reconstructed Radiographs for Solving Inverse Problems in Intraoperative ImagingCode2
PeRFception: Perception using Radiance FieldsCode2
Improving Computed Tomography (CT) Reconstruction via 3D Shape InductionCode0
Adaptive Joint Optimization for 3D Reconstruction with Differentiable Rendering—0
SketchSampler: Sketch-based 3D Reconstruction via View-dependent Depth SamplingCode1
MD-Net: Multi-Detector for Local Feature Extraction—0
Visual-Inertial Multi-Instance Dynamic SLAM with Object-level RelocalisationCode1
PlaneFormers: From Sparse View Planes to 3D ReconstructionCode1
Disentangling 3D Attributes from a Single 2D Image: Human Pose, Shape and Garment—0
MVSFormer: Multi-View Stereo by Learning Robust Image Features and Temperature-based DepthCode2
Learning Object Manipulation Skills from Video via Approximate Differentiable PhysicsCode0
Few-shot Single-view 3D Reconstruction with Memory Prior Contrastive Network—0
Neural Correspondence Field for Object Pose Estimation—0
The One Where They Reconstructed 3D Humans and Environments in TV Shows—0
Cross-Attention of Disentangled Modalities for 3D Human Mesh Recovery with TransformersCode1
Efficient Pix2Vox++ for 3D Cardiac Reconstruction from 2D echo viewsCode1
Towards the Probabilistic Fusion of Learned Priors into Standard Pipelines for 3D Reconstruction—0
Cost Volume Pyramid Network with Multi-strategies Range Searching for Multi-view StereoCode1
DeepFusion: Real-Time Dense 3D Reconstruction for Monocular SLAM using Single-View Depth and Gradient Predictions—0
Visual Speech-Aware Perceptual 3D Facial Expression Reconstruction from VideosCode2
Dense RGB-D-Inertial SLAM with Map Deformations—0
NeurAR: Neural Uncertainty for Autonomous 3D Reconstruction with Implicit Neural Representations—0
R2P: A Deep Learning Model from mmWave Radar to Point Cloud—0
Multi-Event-Camera Depth Estimation and Outlier Rejection by Refocused Events FusionCode1
Neural Pixel Composition: 3D-4D View Synthesis from Multi-Views—0
Perspective Phase Angle Model for Polarimetric 3D ReconstructionCode1
Object-Compositional Neural Implicit SurfacesCode1
Structural Causal 3D Reconstruction—0
2D GANs Meet Unsupervised Single-view 3D Reconstruction—0
VoloGAN: Adversarial Domain Adaptation for Synthetic Depth DataCode0
Efficient View Clustering and Selection for City-Scale 3D Reconstruction—0
Revisiting PatchMatch Multi-View Stereo for Urban 3D Reconstruction—0
Edge-preserving Near-light Photometric Stereo with Neural Surfaces—0
Learning-based Monocular 3D Reconstruction of Birds: A Contemporary Survey—0
Few 'Zero Level Set'-Shot Learning of Shape Signed Distance Functions in Feature SpaceCode0
Vision Transformers: State of the Art and Research Challenges—0
What Makes for Automatic Reconstruction of Pulmonary SegmentsCode0
Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic SurgeryCode2
NeuRIS: Neural Reconstruction of Indoor Scenes Using Normal PriorsCode2
Show:102550
← PrevPage 27 of 47Next →
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