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 426–450 of 2326 papers

TitleStatusHype
Generalized Binary Search Network for Highly-Efficient Multi-View StereoCode1
CoNeRF: Controllable Neural Radiance FieldsCode1
3D Reconstruction Using a Linear Laser Scanner and a CameraCode1
VoRTX: Volumetric 3D Reconstruction With Transformers for Voxelwise View Selection and FusionCode1
Generating Diverse 3D Reconstructions from a Single Occluded Face ImageCode1
MonoScene: Monocular 3D Semantic Scene CompletionCode1
3DVNet: Multi-View Depth Prediction and Volumetric RefinementCode1
A Dataset-Dispersion Perspective on Reconstruction Versus Recognition in Single-View 3D Reconstruction NetworksCode1
Motion-from-Blur: 3D Shape and Motion Estimation of Motion-blurred Objects in VideosCode1
TransMVSNet: Global Context-aware Multi-view Stereo Network with TransformersCode1
Gradient-SDF: A Semi-Implicit Surface Representation for 3D ReconstructionCode1
VaxNeRF: Revisiting the Classic for Voxel-Accelerated Neural Radiance FieldCode1
TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view StereoCode1
FaceScape: 3D Facial Dataset and Benchmark for Single-View 3D Face ReconstructionCode1
UltraPose: Synthesizing Dense Pose with 1 Billion Points by Human-body Decoupling 3D ModelCode1
IVS3D: An Open Source Framework for Intelligent Video Sampling and Preprocessing to Facilitate 3D ReconstructionCode1
AIR-Nets: An Attention-Based Framework for Locally Conditioned Implicit RepresentationsCode1
NeuralBlox: Real-Time Neural Representation Fusion for Robust Volumetric MappingCode1
3D-RETR: End-to-End Single and Multi-View 3D Reconstruction with TransformersCode1
NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the WildCode1
ABO: Dataset and Benchmarks for Real-World 3D Object UnderstandingCode1
Camera Calibration through Camera Projection LossCode1
Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the WildCode1
PDC-Net+: Enhanced Probabilistic Dense Correspondence NetworkCode1
Toward Realistic Single-View 3D Object Reconstruction with Unsupervised Learning from Multiple ImagesCode1
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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