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 1926–1950 of 2326 papers

TitleStatusHype
CCD-3DR: Consistent Conditioning in Diffusion for Single-Image 3D Reconstruction—0
CCL-LGS: Contrastive Codebook Learning for 3D Language Gaussian Splatting—0
CD^2: Fine-grained 3D Mesh Reconstruction With Twice Chamfer Distance—0
Stereo-Based 3D Reconstruction of Dynamic Fluid Surfaces by Global Optimization—0
CDI3D: Cross-guided Dense-view Interpolation for 3D Reconstruction—0
CD-NGP: A Fast Scalable Continual Representation for Dynamic Scenes—0
ALTO: Alternating Latent Topologies for Implicit 3D Reconstruction—0
Cephalogram Synthesis and Landmark Detection in Dental Cone-Beam CT Systems—0
C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds—0
CharNeRF: 3D Character Generation from Concept Art—0
Alligat0R: Pre-Training Through Co-Visibility Segmentation for Relative Camera Pose Regression—0
CHROME: Clothed Human Reconstruction with Occlusion-Resilience and Multiview-Consistency from a Single Image—0
Stereo-based terrain traversability analysis using normal-based segmentation and superpixel surface analysis—0
Class Specific 3D Object Shape Priors Using Surface Normals—0
Clean-NeRF: Reformulating NeRF to account for View-Dependent Observations—0
Clustering Assisted Fundamental Matrix Estimation—0
Stereo camera system calibration: the need of two sets of parameters—0
StereoDRNet: Dilated Residual Stereo Net—0
StereoDRNet: Dilated Residual StereoNet—0
Coded Illumination for 3D Lensless Imaging—0
CodeMapping: Real-Time Dense Mapping for Sparse SLAM using Compact Scene Representations—0
Coherence As Texture - Passive Textureless 3D Reconstruction by Self-interference—0
Coherent3D: Coherent 3D Portrait Video Reconstruction via Triplane Fusion—0
Coherent 3D Portrait Video Reconstruction via Triplane Fusion—0
Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras—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