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 1501–1550 of 2326 papers

TitleStatusHype
MV-DeepSDF: Implicit Modeling with Multi-Sweep Point Clouds for 3D Vehicle Reconstruction in Autonomous Driving—0
MVDiff: Scalable and Flexible Multi-View Diffusion for 3D Object Reconstruction from Single-View—0
MVDiffusion++: A Dense High-resolution Multi-view Diffusion Model for Single or Sparse-view 3D Object Reconstruction—0
MVG-Splatting: Multi-View Guided Gaussian Splatting with Adaptive Quantile-Based Geometric Consistency Densification—0
MVImgNet2.0: A Larger-scale Dataset of Multi-view Images—0
MVLayoutNet:3D layout reconstruction with multi-view panoramas—0
MVSBoost: An Efficient Point Cloud-based 3D Reconstruction—0
3D Reconstruction of unstained cells from a single defocused hologram—0
3D Reconstruction of Transparent Objects With Position-Normal Consistency—0
3D Reconstruction of the Human Colon from Capsule Endoscope Video—0
3D Reconstruction of Temples in the Special Region of Yogyakarta By Using Close-Range Photogrammetry—0
NC-SDF: Enhancing Indoor Scene Reconstruction Using Neural SDFs with View-Dependent Normal Compensation—0
NeAS: 3D Reconstruction from X-ray Images using Neural Attenuation Surface—0
Trick-GS: A Balanced Bag of Tricks for Efficient Gaussian Splatting—0
2D Amodal Instance Segmentation Guided by 3D Shape Prior—0
Patient-Specific Dynamic Digital-Physical Twin for Coronary Intervention Training: An Integrated Mixed Reality Approach—0
NeMo: Learning 3D Neural Motion Fields From Multiple Video Instances of the Same Action—0
Towards Comprehensive Monocular Depth Estimation: Multiple Heads Are Better Than One—0
3D reconstruction from spherical images: A review of techniques, applications, and prospects—0
NERFBK: A High-Quality Benchmark for NERF-Based 3D Reconstruction—0
NeRFlex: Resource-aware Real-time High-quality Rendering of Complex Scenes on Mobile Devices—0
NeRF: Neural Radiance Field in 3D Vision, A Comprehensive Review—0
3D Reconstruction of Simple Objects from A Single View Silhouette Image—0
NeRF-US: Removing Ultrasound Imaging Artifacts from Neural Radiance Fields in the Wild—0
TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo—0
NeRSP: Neural 3D Reconstruction for Reflective Objects with Sparse Polarized Images—0
3D Reconstruction of Shoes for Augmented Reality—0
TSGS: Improving Gaussian Splatting for Transparent Surface Reconstruction via Normal and De-lighting Priors—0
Neural Correspondence Field for Object Pose Estimation—0
TT3D: Table Tennis 3D Reconstruction—0
Neural Fields as Learnable Kernels for 3D Reconstruction—0
Neural Fields for 3D Tracking of Anatomy and Surgical Instruments in Monocular Laparoscopic Video Clips—0
One-Shot Neural Fields for 3D Object Understanding—0
3D Reconstruction of Protein Structures from Multi-view AFM Images using Neural Radiance Fields (NeRFs)—0
3D Reconstruction of Protein Complex Structures Using Synthesized Multi-View AFM Images—0
Neural Fields meet Explicit Geometric Representation for Inverse Rendering of Urban Scenes—0
Neural Fields Meet Explicit Geometric Representations for Inverse Rendering of Urban Scenes—0
Tunnel Surface 3D Reconstruction from Unoriented Image Sequences—0
Neural Implicit Surface Reconstruction using Imaging Sonar—0
Neural Inverse Rendering from Propagating Light—0
Neural Kaleidoscopic Space Sculpting—0
Neural Lens Modeling—0
3D Reconstruction of non-visible surfaces of objects from a Single Depth View -- Comparative Study—0
Neurally Integrated Finite Elements for Differentiable Elasticity on Evolving Domains—0
Neural Network-Based Tracking and 3D Reconstruction of Baseball Pitch Trajectories from Single-View 2D Video—0
NeuralOCT: Airway OCT Analysis via Neural Fields—0
Neural Pixel Composition: 3D-4D View Synthesis from Multi-Views—0
Neural Procedural Reconstruction for Residential Buildings—0
Neural Pruning for 3D Scene Reconstruction: Efficient NeRF Acceleration—0
Neural Radiance Field in Autonomous Driving: A Survey—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