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 451500 of 2326 papers

TitleStatusHype
A Bayesian approach for extracting free energy profiles from cryo-electron microscopy experiments using a path collective variableCode1
Free3D: Consistent Novel View Synthesis without 3D RepresentationCode1
Ref-NeuS: Ambiguity-Reduced Neural Implicit Surface Learning for Multi-View Reconstruction with ReflectionCode1
Creative Birds: Self-Supervised Single-View 3D Style TransferCode1
3DInvNet: A Deep Learning-Based 3D Ground-Penetrating Radar Data InversionCode1
Attention Aware Cost Volume Pyramid Based Multi-view Stereo Network for 3D ReconstructionCode1
Cross3DVG: Cross-Dataset 3D Visual Grounding on Different RGB-D ScansCode1
Cross-Attention of Disentangled Modalities for 3D Human Mesh Recovery with TransformersCode1
Rethinking Content and Style: Exploring Bias for Unsupervised DisentanglementCode1
AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo NetworkCode1
CryoBench: Diverse and challenging datasets for the heterogeneity problem in cryo-EMCode1
RFNet-4D++: Joint Object Reconstruction and Flow Estimation from 4D Point Clouds with Cross-Attention Spatio-Temporal FeaturesCode1
Few-Shot Single-View 3-D Object Reconstruction with Compositional PriorsCode1
DEFN: Dual-Encoder Fourier Group Harmonics Network for Three-Dimensional Indistinct-Boundary Object SegmentationCode1
Deep Learning-based Bathymetry Retrieval without In-situ Depths using Remote Sensing Imagery and SfM-MVS DSMs with Data GapsCode1
CT-MVSNet: Efficient Multi-View Stereo with Cross-scale TransformerCode1
FineRecon: Depth-aware Feed-forward Network for Detailed 3D ReconstructionCode1
Deep Two-View Structure-from-Motion RevisitedCode1
Generalized Binary Search Network for Highly-Efficient Multi-View StereoCode1
Curvature-guided dynamic scale networks for Multi-view StereoCode1
Fast and Lightweight Scene Regressor for Camera RelocalizationCode1
Scan2LoD3: Reconstructing semantic 3D building models at LoD3 using ray casting and Bayesian networksCode1
Fast and Robust Iterative Closest PointCode1
SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static ImagesCode1
3D Magic Mirror: Clothing Reconstruction from a Single Image via a Causal PerspectiveCode1
Self-Evolving Neural Radiance FieldsCode1
FaceScape: 3D Facial Dataset and Benchmark for Single-View 3D Face ReconstructionCode1
Self-Supervised Super-Plane for Neural 3D ReconstructionCode1
FaceOcc: A Diverse, High-quality Face Occlusion Dataset for Human Face ExtractionCode1
EvGGS: A Collaborative Learning Framework for Event-based Generalizable Gaussian SplattingCode1
EventEgo3D: 3D Human Motion Capture from Egocentric Event StreamsCode1
Explicit and Implicit Representations in AI-based 3D Reconstruction for Radiology: A Systematic ReviewCode1
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
DeepFaceFlow: In-the-wild Dense 3D Facial Motion EstimationCode1
Extremely Dense Point Correspondences using a Learned Feature DescriptorCode1
3DVNet: Multi-View Depth Prediction and Volumetric RefinementCode1
Evaluate Geometry of Radiance Fields with Low-frequency Color PriorCode1
Decomposing NeRF for Editing via Feature Field DistillationCode1
Enhance-NeRF: Multiple Performance Evaluation for Neural Radiance FieldsCode1
Enhancing Agricultural Environment Perception via Active Vision and Zero-Shot LearningCode1
SMART: Spatial Modeling Algorithms for Reaction and TransportCode1
Sources of Uncertainty in 3D Scene ReconstructionCode1
ASLFeat: Learning Local Features of Accurate Shape and LocalizationCode1
3D Object Reconstruction from Hand-Object InteractionsCode1
ENRICH: Multi-purposE dataset for beNchmaRking In Computer vision and pHotogrammetryCode1
Event-based Stereo Visual OdometryCode1
InFusionSurf: Refining Neural RGB-D Surface Reconstruction Using Per-Frame Intrinsic Refinement and TSDF Fusion Prior LearningCode1
Efficient Implicit Neural Reconstruction Using LiDARCode1
E3D: Event-Based 3D Shape ReconstructionCode1
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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