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 1651–1700 of 2326 papers

TitleStatusHype
SDL-MVS: View Space and Depth Deformable Learning Paradigm for Multi-View Stereo Reconstruction in Remote Sensing—0
SD-MVS: Segmentation-Driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization—0
SE(3) Equivariant Convolution and Transformer in Ray Space—0
SE(3) Equivariant Convolution and Transformer in Ray Space—0
Equivariant Light Field Convolution and Transformer—0
Seafloor-Invariant Caustics Removal from Underwater Imagery—0
Seamless Augmented Reality Integration in Arthroscopy: A Pipeline for Articular Reconstruction and Guidance—0
Second-order Anisotropic Gaussian Directional Derivative Filters for Blob Detection—0
Seeing A 3D World in A Grain of Sand—0
ViKiNG: Vision-Based Kilometer-Scale Navigation with Geographic Hints—0
SeFM: A Sequential Feature Point Matching Algorithm for Object 3D Reconstruction—0
Segmentation-Guided Neural Radiance Fields for Novel Street View Synthesis—0
Segment Based 3D Object Shape Priors—0
SegNeRF: 3D Part Segmentation with Neural Radiance Fields—0
AugGS: Self-augmented Gaussians with Structural Masks for Sparse-view 3D Reconstruction—0
VIN-NBV: A View Introspection Network for Next-Best-View Selection for Resource-Efficient 3D Reconstruction—0
Self-expressive Dictionary Learning for Dynamic 3D Reconstruction—0
Self-optimizing loop sifting and majorization for 3D reconstruction—0
SelfSplat: Pose-Free and 3D Prior-Free Generalizable 3D Gaussian Splatting—0
Self-Supervised 3D Mesh Reconstruction From Single Images—0
Self-supervised Dense 3D Reconstruction from Monocular Endoscopic Video—0
Self-supervised Depth Denoising Using Lower- and Higher-quality RGB-D sensors—0
Self-supervised Fetal MRI 3D Reconstruction Based on Radiation Diffusion Generation Model—0
Self-Supervised Generative Adversarial Network for Depth Estimation in Laparoscopic Images—0
Self-Supervised Object-in-Gripper Segmentation from Robotic Motions—0
VIO-Aided Structure from Motion Under Challenging Environments—0
Virtual Correspondence: Humans as a Cue for Extreme-View Geometry—0
Self-Supervised Surgical Instrument 3D Reconstruction from a Single Camera Image—0
Semantic 3D Reconstruction with Finite Element Bases—0
Semantically Aware Urban 3D Reconstruction with Plane-Based Regularization—0
Semantically Coherent Co-Segmentation and Reconstruction of Dynamic Scenes—0
Semantically Informed Multiview Surface Refinement—0
Semantic and Articulated Pedestrian Sensing Onboard a Moving Vehicle—0
Semantic Communication-Enabled Cloud-Edge-End-collaborative Metaverse Services Architecure—0
Semantic Multi-View Stereo: Jointly Estimating Objects and Voxels—0
SemanticSplat: Feed-Forward 3D Scene Understanding with Language-Aware Gaussian Fields—0
Virtual Rephotography: Novel View Prediction Error for 3D Reconstruction—0
Semi-Calibrated Near Field Photometric Stereo—0
Zero-P-to-3: Zero-Shot Partial-View Images to 3D Object—0
Semi-Dense 3D Semantic Mapping from Monocular SLAM—0
Semi-supervised Dense Keypoints Using Unlabeled Multiview Images—0
Vision-Language Embodiment for Monocular Depth Estimation—0
SemStereo: Semantic-Constrained Stereo Matching Network for Remote Sensing—0
S-EO: A Large-Scale Dataset for Geometry-Aware Shadow Detection in Remote Sensing Applications—0
Separating Overlapping Tissue Layers from Microscopy Images—0
Serialized Point Mamba: A Serialized Point Cloud Mamba Segmentation Model—0
Vision Transformers: State of the Art and Research Challenges—0
Set Distribution Networks: a Generative Model for Sets of Images—0
SG-GAN: Fine Stereoscopic-Aware Generation for 3D Brain Point Cloud Up-sampling from a Single Image—0
SHaDe: Compact and Consistent Dynamic 3D Reconstruction via Tri-Plane Deformation and Latent Diffusion—0
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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