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 226250 of 2326 papers

TitleStatusHype
Generative Object Insertion in Gaussian Splatting with a Multi-View Diffusion ModelCode1
Matérn Kernels for Tunable Implicit Surface ReconstructionCode1
Enhancing Agricultural Environment Perception via Active Vision and Zero-Shot LearningCode1
Sources of Uncertainty in 3D Scene ReconstructionCode1
Online 3D reconstruction and dense tracking in endoscopic videosCode1
DARES: Depth Anything in Robotic Endoscopic Surgery with Self-supervised Vector-LoRA of the Foundation ModelCode1
Mismatched: Evaluating the Limits of Image Matching Approaches and BenchmarksCode1
S4D: Streaming 4D Real-World Reconstruction with Gaussians and 3D Control PointsCode1
Comparative Evaluation of 3D Reconstruction Methods for Object Pose EstimationCode1
CryoBench: Diverse and challenging datasets for the heterogeneity problem in cryo-EMCode1
A Review of 3D Reconstruction Techniques for Deformable Tissues in Robotic SurgeryCode1
Opening the Black Box of 3D Reconstruction Error Analysis with VECTORCode1
BodySLAM: A Generalized Monocular Visual SLAM Framework for Surgical ApplicationsCode1
SparseCraft: Few-Shot Neural Reconstruction through Stereopsis Guided Geometric LinearizationCode1
MaRINeR: Enhancing Novel Views by Matching Rendered Images with Nearby ReferencesCode1
Repeat and Concatenate: 2D to 3D Image Translation with 3D to 3D Generative ModelingCode1
E2GS: Event Enhanced Gaussian SplattingCode1
A Two-Stage Masked Autoencoder Based Network for Indoor Depth CompletionCode1
HO-Cap: A Capture System and Dataset for 3D Reconstruction and Pose Tracking of Hand-Object InteractionCode1
Coarse-To-Fine Tensor Trains for Compact Visual RepresentationsCode1
C^2RV: Cross-Regional and Cross-View Learning for Sparse-View CBCT ReconstructionCode1
EvGGS: A Collaborative Learning Framework for Event-based Generalizable Gaussian SplattingCode1
S3O: A Dual-Phase Approach for Reconstructing Dynamic Shape and Skeleton of Articulated Objects from Single Monocular VideoCode1
TD-NeRF: Novel Truncated Depth Prior for Joint Camera Pose and Neural Radiance Field OptimizationCode1
OneTo3D: One Image to Re-editable Dynamic 3D Model and Video GenerationCode1
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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