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 51–75 of 2326 papers

TitleStatusHype
MR2US-Pro: Prostate MR to Ultrasound Image Translation and Registration Based on Diffusion Models—0
SR3D: Unleashing Single-view 3D Reconstruction for Transparent and Specular Object Grasping—0
Radiant Triangle Soup with Soft Connectivity Forces for 3D Reconstruction and Novel View Synthesis—0
PhysicsNeRF: Physics-Guided 3D Reconstruction from Sparse ViewsCode0
SpatialSplat: Efficient Semantic 3D from Sparse Unposed Images—0
Zero-P-to-3: Zero-Shot Partial-View Images to 3D Object—0
PS4PRO: Pixel-to-pixel Supervision for Photorealistic Rendering and Optimization—0
OmniIndoor3D: Comprehensive Indoor 3D Reconstruction—0
CCL-LGS: Contrastive Codebook Learning for 3D Language Gaussian Splatting—0
ParticleGS: Particle-Based Dynamics Modeling of 3D Gaussians for Prior-free Motion ExtrapolationCode1
OB3D: A New Dataset for Benchmarking Omnidirectional 3D Reconstruction Using BlenderCode1
VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D ReconstructionCode3
ErpGS: Equirectangular Image Rendering enhanced with 3D Gaussian Regularization—0
Sparse2DGS: Sparse-View Surface Reconstruction using 2D Gaussian Splatting with Dense Point Cloud—0
HaloGS: Loose Coupling of Compact Geometry and Gaussian Splats for 3D Scenes—0
Towards Dynamic 3D Reconstruction of Hand-Instrument Interaction in Ophthalmic Surgery—0
Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse AttentionCode5
Is Single-View Mesh Reconstruction Ready for Robotics?—0
From Flight to Insight: Semantic 3D Reconstruction for Aerial Inspection via Gaussian Splatting and Language-Guided Segmentation—0
SHaDe: Compact and Consistent Dynamic 3D Reconstruction via Tri-Plane Deformation and Latent Diffusion—0
GS2E: Gaussian Splatting is an Effective Data Generator for Event Stream Generation—0
3D Reconstruction from Sketches—0
Sparc3D: Sparse Representation and Construction for High-Resolution 3D Shapes Modeling—0
AppleGrowthVision: A large-scale stereo dataset for phenological analysis, fruit detection, and 3D reconstruction in apple orchards—0
From Low Field to High Value: Robust Cortical Mapping from Low-Field MRI—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