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

Showing 426450 of 2326 papers

TitleStatusHype
A Bayesian approach for extracting free energy profiles from cryo-electron microscopy experiments using a path collective variableCode1
Learning Online Multi-Sensor Depth FusionCode1
Progressive Volume Distillation with Active Learning for Efficient NeRF Architecture ConversionCode1
ConcealGS: Concealing Invisible Copyright Information in 3D Gaussian SplattingCode1
Attention Aware Cost Volume Pyramid Based Multi-view Stereo Network for 3D ReconstructionCode1
Learning to Detect 3D Reflection Symmetry for Single-View ReconstructionCode1
CoNeRF: Controllable Neural Radiance FieldsCode1
AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo NetworkCode1
Learning to Parse Wireframes in Images of Man-Made EnvironmentsCode1
DiffInDScene: Diffusion-based High-Quality 3D Indoor Scene GenerationCode1
ConsistentNeRF: Enhancing Neural Radiance Fields with 3D Consistency for Sparse View SynthesisCode1
Level-S^2fM: Structure from Motion on Neural Level Set of Implicit SurfacesCode1
Leveraging Photogrammetric Mesh Models for Aerial-Ground Feature Point Matching Toward Integrated 3D ReconstructionCode1
NeuralBlox: Real-Time Neural Representation Fusion for Robust Volumetric MappingCode1
O^2-Recon: Completing 3D Reconstruction of Occluded Objects in the Scene with a Pre-trained 2D Diffusion ModelCode1
Deformable Model-Driven Neural Rendering for High-Fidelity 3D Reconstruction of Human Heads Under Low-View SettingsCode1
NeMo: 3D Neural Motion Fields from Multiple Video Instances of the Same ActionCode1
DEFN: Dual-Encoder Fourier Group Harmonics Network for Three-Dimensional Indistinct-Boundary Object SegmentationCode1
Convolutional Occupancy NetworksCode1
Coordinate Quantized Neural Implicit Representations for Multi-view ReconstructionCode1
Living Scenes: Multi-object Relocalization and Reconstruction in Changing 3D EnvironmentsCode1
Deep Two-View Structure-from-Motion RevisitedCode1
NeAT: Neural Adaptive TomographyCode1
3D Pose Estimation of Two Interacting Hands from a Monocular Event CameraCode1
A Survey on 3D Reconstruction Techniques in Plant Phenotyping: From Classical Methods to Neural Radiance Fields (NeRF), 3D Gaussian Splatting (3DGS), and BeyondCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
13D-R2N2Overall0.63Unverified
2GipumaOverall0.58Unverified
3COLMAPOverall0.53Unverified
4MVSNetOverall0.46Unverified
5Vis-MVSNetOverall0.37Unverified
6AA-RMVSNetOverall0.36Unverified
7Cas-MVSNetOverall0.36Unverified
8EPP-MVSNetOverall0.36Unverified
9PatchmatchNetOverall0.35Unverified
10CVP-MVSNetOverall0.35Unverified
#ModelMetricClaimedVerifiedStatus
1MD-GONIoU92.8Unverified
2POCOIoU92.6Unverified
3FS-SDFIoU91.2Unverified
4DP-ConvONetIoU89.5Unverified
5ConvONetIoU88.4Unverified
6ONetIoU76.1Unverified
7EVolTIoU73.8Unverified
8ZubicLioIoU65.43Unverified
#ModelMetricClaimedVerifiedStatus
1AttSets3DIoU0.64Unverified
2PSGN3DIoU0.64Unverified
3OGN3DIoU0.6Unverified
43D-R2N23DIoU0.56Unverified
#ModelMetricClaimedVerifiedStatus
1Scan2CADAverage Accuracy31.68Unverified
23DMatchAverage Accuracy10.29Unverified
#ModelMetricClaimedVerifiedStatus
1SVCPChamfer10Unverified
#ModelMetricClaimedVerifiedStatus
1EVLAccuracy18.2Unverified
#ModelMetricClaimedVerifiedStatus
1EVLAccuracy5.7Unverified
#ModelMetricClaimedVerifiedStatus
1Atlas (finetuned)3DIoU89.4Unverified