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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1526–1550 of 2326 papers

TitleStatusHype
RANSAC based three points algorithm for ellipse fitting of spherical object's projection—0
RapidVol: Rapid Reconstruction of 3D Ultrasound Volumes from Sensorless 2D Scans—0
ZeroGrasp: Zero-Shot Shape Reconstruction Enabled Robotic Grasping—0
RayTran: 3D pose estimation and shape reconstruction of multiple objects from videos with ray-traced transformers—0
RDD: Robust Feature Detector and Descriptor using Deformable Transformer—0
RDG-GS: Relative Depth Guidance with Gaussian Splatting for Real-time Sparse-View 3D Rendering—0
3DMiner: Discovering Shapes from Large-Scale Unannotated Image Datasets—0
3D Mesh Editing using Masked LRMs—0
RealFusion: 360deg Reconstruction of Any Object From a Single Image—0
Real-Time 3D Reconstruction of Colonoscopic Surfaces for Determining Missing Regions—0
Real-time 3D Reconstruction on Construction Site using Visual SLAM and UAV—0
Real-Time 3D Shape of Micro-Details—0
Realtime CNN-based Keypoint Detector with Sobel Filter and CNN-based Descriptor Trained with Keypoint Candidates—0
Using 3D reconstruction from image motion to predict total leaf area in dwarf tomato plants—0
Real-time dense 3D Reconstruction from monocular video data captured by low-cost UAVs—0
Hierarchical Procedural Framework for Low-latency Robot-Assisted Hand-Object Interaction—0
Real Time Incremental Image Mosaicking Without Use of Any Camera Parameter—0
Real-time Indoor Scene Reconstruction with RGBD and Inertia Input—0
Using 3D Topological Connectivity for Ghost Particle Reduction in Flow Reconstruction—0
Recent Advances in 3D Gaussian Splatting—0
Recent Trends in 3D Reconstruction of General Non-Rigid Scenes—0
RecGS: Removing Water Caustic with Recurrent Gaussian Splatting—0
ReconFusion: 3D Reconstruction with Diffusion Priors—0
Reconstructing 3D Model from Single-View Sketch with Deep Neural Network—0
Reconstructing and grounding narrated instructional videos in 3D—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