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 151–200 of 2326 papers

TitleStatusHype
Multi-View Mesh Reconstruction with Neural Deferred ShadingCode2
SDFusion: Multimodal 3D Shape Completion, Reconstruction, and GenerationCode2
SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance FieldsCode2
NeuralLift-360: Lifting An In-the-wild 2D Photo to A 3D Object with 360° ViewsCode2
Fast-SNARF: A Fast Deformer for Articulated Neural FieldsCode2
Shape, Pose, and Appearance from a Single Image via Bootstrapped Radiance Field InversionCode2
ESLAM: Efficient Dense SLAM System Based on Hybrid Representation of Signed Distance FieldsCode2
RenderDiffusion: Image Diffusion for 3D Reconstruction, Inpainting and GenerationCode2
Visual Language Maps for Robot NavigationCode2
SHINE-Mapping: Large-Scale 3D Mapping Using Sparse Hierarchical Implicit Neural RepresentationsCode2
Fast Auto-Differentiable Digitally Reconstructed Radiographs for Solving Inverse Problems in Intraoperative ImagingCode2
PeRFception: Perception using Radiance FieldsCode2
MVSFormer: Multi-View Stereo by Learning Robust Image Features and Temperature-based DepthCode2
Visual Speech-Aware Perceptual 3D Facial Expression Reconstruction from VideosCode2
Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic SurgeryCode2
NeuRIS: Neural Reconstruction of Indoor Scenes Using Normal PriorsCode2
Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and DenoisingCode2
MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface ReconstructionCode2
Neural 3D Reconstruction in the WildCode2
Neural 3D Scene Reconstruction with the Manhattan-world AssumptionCode2
ARCTIC: A Dataset for Dexterous Bimanual Hand-Object ManipulationCode2
Power Bundle Adjustment for Large-Scale 3D ReconstructionCode2
EMOCA: Emotion Driven Monocular Face Capture and AnimationCode2
DAD-3DHeads: A Large-scale Dense, Accurate and Diverse Dataset for 3D Head Alignment from a Single ImageCode2
NeRFusion: Fusing Radiance Fields for Large-Scale Scene ReconstructionCode2
OcclusionFusion: Occlusion-aware Motion Estimation for Real-time Dynamic 3D ReconstructionCode2
CenterSnap: Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size EstimationCode2
Rethinking Depth Estimation for Multi-View Stereo: A Unified RepresentationCode2
POCO: Point Convolution for Surface ReconstructionCode2
Neural Fields in Visual Computing and BeyondCode2
Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category ReconstructionCode2
Kimera: from SLAM to Spatial Perception with 3D Dynamic Scene GraphsCode2
Learning Continuous Image Representation with Local Implicit Image FunctionCode2
pixelNeRF: Neural Radiance Fields from One or Few ImagesCode2
Unpaired Motion Style Transfer from Video to AnimationCode2
Learning Implicit Surface Light FieldsCode2
Atlas: End-to-End 3D Scene Reconstruction from Posed ImagesCode2
3D Dynamic Scene Graphs: Actionable Spatial Perception with Places, Objects, and HumansCode2
SurgTPGS: Semantic 3D Surgical Scene Understanding with Text Promptable Gaussian SplattingCode1
DeOcc-1-to-3: 3D De-Occlusion from a Single Image via Self-Supervised Multi-View DiffusionCode1
MCN-SLAM: Multi-Agent Collaborative Neural SLAM with Hybrid Implicit Neural Scene RepresentationCode1
R3eVision: A Survey on Robust Rendering, Restoration, and Enhancement for 3D Low-Level VisionCode1
OGGSplat: Open Gaussian Growing for Generalizable Reconstruction with Expanded Field-of-ViewCode1
OB3D: A New Dataset for Benchmarking Omnidirectional 3D Reconstruction Using BlenderCode1
ParticleGS: Particle-Based Dynamics Modeling of 3D Gaussians for Prior-free Motion ExtrapolationCode1
RefRef: A Synthetic Dataset and Benchmark for Reconstructing Refractive and Reflective ObjectsCode1
A Survey on 3D Reconstruction Techniques in Plant Phenotyping: From Classical Methods to Neural Radiance Fields (NeRF), 3D Gaussian Splatting (3DGS), and BeyondCode1
Mesh-Learner: Texturing Mesh with Spherical HarmonicsCode1
PerfCam: Digital Twinning for Production Lines Using 3D Gaussian Splatting and Vision ModelsCode1
Deep Learning-based Bathymetry Retrieval without In-situ Depths using Remote Sensing Imagery and SfM-MVS DSMs with Data GapsCode1
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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