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 12511275 of 2326 papers

TitleStatusHype
Multi-view Tracking, Re-ID, and Social Network Analysis of a Flock of Visually Similar Birds in an Outdoor Aviary0
MuSHRoom: Multi-Sensor Hybrid Room Dataset for Joint 3D Reconstruction and Novel View Synthesis0
3D Reconstruction of Whole Stomach from Endoscope Video Using Structure-from-Motion0
MVBoost: Boost 3D Reconstruction with Multi-View Refinement0
MVD^2: Efficient Multiview 3D Reconstruction for Multiview Diffusion0
MV-DeepSDF: Implicit Modeling with Multi-Sweep Point Clouds for 3D Vehicle Reconstruction in Autonomous Driving0
MVDiff: Scalable and Flexible Multi-View Diffusion for 3D Object Reconstruction from Single-View0
MVDiffusion++: A Dense High-resolution Multi-view Diffusion Model for Single or Sparse-view 3D Object Reconstruction0
MVG-Splatting: Multi-View Guided Gaussian Splatting with Adaptive Quantile-Based Geometric Consistency Densification0
MVImgNet2.0: A Larger-scale Dataset of Multi-view Images0
MVLayoutNet:3D layout reconstruction with multi-view panoramas0
MVSBoost: An Efficient Point Cloud-based 3D Reconstruction0
3D Reconstruction of unstained cells from a single defocused hologram0
3D Reconstruction of Transparent Objects With Position-Normal Consistency0
3D Reconstruction of the Human Colon from Capsule Endoscope Video0
3D Reconstruction of Temples in the Special Region of Yogyakarta By Using Close-Range Photogrammetry0
NC-SDF: Enhancing Indoor Scene Reconstruction Using Neural SDFs with View-Dependent Normal Compensation0
NeAS: 3D Reconstruction from X-ray Images using Neural Attenuation Surface0
Trick-GS: A Balanced Bag of Tricks for Efficient Gaussian Splatting0
2D Amodal Instance Segmentation Guided by 3D Shape Prior0
Patient-Specific Dynamic Digital-Physical Twin for Coronary Intervention Training: An Integrated Mixed Reality Approach0
NeMo: Learning 3D Neural Motion Fields From Multiple Video Instances of the Same Action0
Towards Comprehensive Monocular Depth Estimation: Multiple Heads Are Better Than One0
3D reconstruction from spherical images: A review of techniques, applications, and prospects0
NERFBK: A High-Quality Benchmark for NERF-Based 3D Reconstruction0
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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