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 14511475 of 2326 papers

TitleStatusHype
Multi-view Monocular Depth and Uncertainty Prediction with Deep SfM in Dynamic Environments0
FaceOcc: A Diverse, High-quality Face Occlusion Dataset for Human Face ExtractionCode1
Instant Neural Graphics Primitives with a Multiresolution Hash EncodingCode6
Automated Aircraft Dent Inspection via a Modified Fourier Transform Profilometry AlgorithmCode1
POCO: Point Convolution for Surface ReconstructionCode2
Rethinking Depth Estimation for Multi-View Stereo: A Unified RepresentationCode2
Blind Face Restoration via Integrating Face Shape and Generative Priors0
Using 3D Topological Connectivity for Ghost Particle Reduction in Flow Reconstruction0
KeyTr: Keypoint Transporter for 3D Reconstruction of Deformable Objects in Videos0
Learning Soft Estimator of Keypoint Scale and Orientation With Probabilistic Covariant LossCode0
f-SfT: Shape-From-Template With a Physics-Based Deformation ModelCode1
Enhancing Face Recognition With Self-Supervised 3D Reconstruction0
Automated 3D reconstruction of LoD2 and LoD1 models for all 10 million buildings of the Netherlands0
Visual and Object Geo-localization: A Comprehensive Survey0
ACDNet: Adaptively Combined Dilated Convolution for Monocular Panorama Depth EstimationCode1
Multimodal perception for dexterous manipulation0
Multi-initialization Optimization Network for Accurate 3D Human Pose and Shape Estimation0
Pose Adaptive Dual Mixup for Few-Shot Single-View 3D Reconstruction0
Multi-View Partial (MVP) Point Cloud Challenge 2021 on Completion and Registration: Methods and ResultsCode1
ADJUST: A Dictionary-Based Joint Reconstruction and Unmixing Method for Spectral TomographyCode1
MoCaNet: Motion Retargeting in-the-wild via Canonicalization Networks0
Improving neural implicit surfaces geometry with patch warpingCode1
GCNDepth: Self-supervised Monocular Depth Estimation based on Graph Convolutional NetworkCode1
MVLayoutNet:3D layout reconstruction with multi-view panoramas0
Curvature-guided dynamic scale networks for Multi-view StereoCode1
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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