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 1626–1650 of 2326 papers

TitleStatusHype
PERF: Performant, Explicit Radiance Fields—0
What's Behind the Couch? Directed Ray Distance Functions (DRDF) for 3D Scene Reconstruction—0
Input-level Inductive Biases for 3D Reconstruction—0
Fast Organization of Objects' Spatial Positions in Manipulator Space from Single RGB-D CameraCode0
Geometry-aware Two-scale PIFu Representation for Human Reconstruction—0
Dense Keypoints via Multiview Supervision—0
REMIPS: Physically Consistent 3D Reconstruction of Multiple Interacting People under Weak Supervision—0
LatentHuman: Shape-and-Pose Disentangled Latent Representation for Human Bodies—0
ESL: Event-based Structured Light—0
IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions—0
Urban Radiance Fields—0
Exploiting full Resolution Feature Context for Liver Tumor and Vessel Segmentation via Integrate Framework: Application to Liver Tumor and Vessel 3D Reconstruction under embedded microprocessorCode0
Neural Fields as Learnable Kernels for 3D Reconstruction—0
Monocular Road Planar Parallax Estimation—0
ColDE: A Depth Estimation Framework for Colonoscopy Reconstruction—0
Towards Comprehensive Monocular Depth Estimation: Multiple Heads Are Better Than One—0
Pipeline for 3D reconstruction of the human body from AR/VR headset mounted egocentric cameras—0
Towards Panoptic 3D Parsing for Single Image in the Wild—0
Monocular 3D Reconstruction of Interacting Hands via Collision-Aware Factorized Refinements—0
A Comparative Study of Coarse to Dense 3D Indoor Scene Registration Algorithms—0
TMBuD: A dataset for urban scene building detectionCode0
Robust Multi-view Registration of Point Sets with Laplacian Mixture Model—0
High Fidelity 3D Reconstructions with Limited Physical Views—0
Style Agnostic 3D Reconstruction via Adversarial Style Transfer—0
3D Reconstruction of Curvilinear Structures with Stereo Matching DeepConvolutional Neural Networks—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