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 1301–1325 of 2326 papers

TitleStatusHype
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
Neural Radiance Fields Approach to Deep Multi-View Photometric Stereo—0
Neural Radiance Fields for Novel View Synthesis in Monocular Gastroscopy—0
Neural Radiance Fields with Torch Units—0
Turbo-GS: Accelerating 3D Gaussian Fitting for High-Quality Radiance Fields—0
Neural Rendering and Its Hardware Acceleration: A Review—0
Neural Rendering based Urban Scene Reconstruction for Autonomous Driving—0
Neural rendering enables dynamic tomography—0
3D Reconstruction of Non-cooperative Resident Space Objects using Instant NGP-accelerated NeRF and D-NeRF—0
Neural Rerendering in the Wild—0
Neural RGB(r)D Sensing: Depth and Uncertainty From a Video Camera—0
Neural Scene Representation for Locomotion on Structured Terrain—0
Turning Mobile Phones into 3D Scanners—0
NeurAR: Neural Uncertainty for Autonomous 3D Reconstruction with Implicit Neural Representations—0
3D Reconstruction of Multiple Objects by mmWave Radar on UAV—0
NeuSG: Neural Implicit Surface Reconstruction with 3D Gaussian Splatting Guidance—0
NeuVV: Neural Volumetric Videos with Immersive Rendering and Editing—0
Next Best View For Point-Cloud Model Acquisition: Bayesian Approximation and Uncertainty Analysis—0
Two-view 3D Reconstruction for Food Volume Estimation—0
UAV-based Autonomous Image Acquisition with Multi-View Stereo Quality Assurance by Confidence Prediction—0
Noise2Filter: fast, self-supervised learning and real-time reconstruction for 3D Computed Tomography—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