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 1301–1350 of 2326 papers

TitleStatusHype
3D Target Detection and Spectral Classification for Single-photon LiDAR Data—0
TomoSAR-ALISTA: Efficient TomoSAR Imaging via Deep Unfolded Network—0
Learning Efficient Photometric Feature Transform for Multi-view Stereo—0
Learning from the Giants: A Practical Approach to Underwater Depth and Surface Normals Estimation—0
3D Reconstruction of Objects in Hands without Real World 3D Supervision—0
Tool-as-Interface: Learning Robot Policies from Human Tool Usage through Imitation Learning—0
3D Surface Reconstruction with Enhanced High-Frequency Details—0
Learning Inter- and Intraframe Representations for Non-Lambertian Photometric Stereo—0
Learning monocular 3D reconstruction of articulated categories from motion—0
Learning Neural Implicit through Volume Rendering with Attentive Depth Fusion Priors—0
Learning Neural Radiance Fields from Multi-View Geometry—0
Portrait4D: Learning One-Shot 4D Head Avatar Synthesis using Synthetic Data—0
Topologically Consistent Multi-View Face Inference Using Volumetric Sampling—0
3D Surface Reconstruction in the Wild by Deforming Shape Priors from Synthetic Data—0
Learning Perspective Undistortion of Portraits—0
Learning Photometric Feature Transform for Free-form Object Scan—0
Learning Priors for Semantic 3D Reconstruction—0
Learning Spatially Collaged Fourier Bases for Implicit Neural Representation—0
Learning Structural Graph Layouts and 3D Shapes for Long Span Bridges 3D Reconstruction—0
2D GANs Meet Unsupervised Single-view 3D Reconstruction—0
Learning to Generate and Reconstruct 3D Meshes with only 2D Supervision—0
Learning to Guide Local Feature Matches—0
Learning to Infer the Depth Map of a Hand from its Color Image—0
Geometry-aware Two-scale PIFu Representation for Human Reconstruction—0
Learning Topology Uniformed Face Mesh by Volume Rendering for Multi-view Reconstruction—0
Learning to Predict Scene-Level Implicit 3D from Posed RGBD Data—0
Learning to Reconstruct and Understand Indoor Scenes from Sparse Views—0
Learning to Reconstruct Shapes from Unseen Classes—0
Learning Transferable Kinematic Dictionary for 3D Human Pose and Shape Reconstruction—0
X-ray nano-holotomography reconstruction with simultaneous probe retrieval—0
Learning View Priors for Single-view 3D Reconstruction—0
Learning Visibility Field for Detailed 3D Human Reconstruction and Relighting—0
Learning with Noisy Ground Truth: From 2D Classification to 3D Reconstruction—0
Towards a Better Understanding of the Computer Vision Research Community in Africa—0
LetsGo: Large-Scale Garage Modeling and Rendering via LiDAR-Assisted Gaussian Primitives—0
Towards Automatic Digital Documentation and Progress Reporting of Mechanical Construction Pipes using Smartphones—0
Leveraging Stable Diffusion for Monocular Depth Estimation via Image Semantic Encoding—0
Towards Automatic SAR-Optical Stereogrammetry over Urban Areas using Very High Resolution Imagery—0
Leveraging Vision Reconstruction Pipelines for Satellite Imagery—0
3D Surface Detail Enhancement From a Single Normal Map—0
Monocular Outdoor Semantic Mapping with a Multi-task Network—0
LiftImage3D: Lifting Any Single Image to 3D Gaussians with Video Generation Priors—0
Lifting Object Detection Datasets into 3D—0
Light3R-SfM: Towards Feed-forward Structure-from-Motion—0
Light Field Imaging in the Restrictive Object Space based on Flexible Angular Plane—0
Light field Rectification based on relative pose estimation—0
3DStyleNet: Creating 3D Shapes with Geometric and Texture Style Variations—0
3D Sketching using Multi-View Deep Volumetric Prediction—0
Likelihood-Scheduled Score-Based Generative Modeling for Fully 3D PET Image Reconstruction—0
LiM-Loc: Visual Localization with Dense and Accurate 3D Reference Maps Directly Corresponding 2D Keypoints to 3D LiDAR Point Clouds—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