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 1–25 of 2326 papers

TitleStatusHype
AutoPartGen: Autogressive 3D Part Generation and Discovery—0
BRUM: Robust 3D Vehicle Reconstruction from 360 Sparse Images—0
SpatialTrackerV2: 3D Point Tracking Made EasyCode4
Towards Depth Foundation Model: Recent Trends in Vision-Based Depth Estimation—0
Binomial Self-Compensation: Mechanism and Suppression of Motion Error in Phase-Shifting Profilometry—0
Review of Feed-forward 3D Reconstruction: From DUSt3R to VGGT—0
An Efficient Approach for Muscle Segmentation and 3D Reconstruction Using Keypoint Tracking in MRI Scan—0
DreamGrasp: Zero-Shot 3D Multi-Object Reconstruction from Partial-View Images for Robotic Manipulation—0
MoReMouse: Monocular Reconstruction of Laboratory Mouse—0
SIU3R: Simultaneous Scene Understanding and 3D Reconstruction Beyond Feature AlignmentCode2
SurgTPGS: Semantic 3D Surgical Scene Understanding with Text Promptable Gaussian SplattingCode1
PanSt3R: Multi-view Consistent Panoptic Segmentation—0
Geometry and Perception Guided Gaussians for Multiview-consistent 3D Generation from a Single Image—0
PoseMaster: Generating 3D Characters in Arbitrary Poses from a Single Image—0
DeOcc-1-to-3: 3D De-Occlusion from a Single Image via Self-Supervised Multi-View DiffusionCode1
EndoFlow-SLAM: Real-Time Endoscopic SLAM with Flow-Constrained Gaussian Splatting—0
Joint attitude estimation and 3D neural reconstruction of non-cooperative space objects—0
Video Perception Models for 3D Scene Synthesis—0
Experimental Assessment of Neural 3D Reconstruction for Small UAV-based Applications—0
MCN-SLAM: Multi-Agent Collaborative Neural SLAM with Hybrid Implicit Neural Scene RepresentationCode1
Mobile Image Analysis Application for Mantoux Skin Test—0
Part^2GS: Part-aware Modeling of Articulated Objects using 3D Gaussian Splatting—0
R3eVision: A Survey on Robust Rendering, Restoration, and Enhancement for 3D Low-Level VisionCode1
RA-NeRF: Robust Neural Radiance Field Reconstruction with Accurate Camera Pose Estimation under Complex Trajectories—0
4Real-Video-V2: Fused View-Time Attention and Feedforward Reconstruction for 4D Scene Generation—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