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 876–900 of 2326 papers

TitleStatusHype
Gaussian Splashing: Direct Volumetric Rendering Underwater—0
DeSplat: Decomposed Gaussian Splatting for Distractor-Free Rendering—0
360Recon: An Accurate Reconstruction Method Based on Depth Fusion from 360 Images—0
RIGI: Rectifying Image-to-3D Generation Inconsistency via Uncertainty-aware Learning—0
Track Anything Behind Everything: Zero-Shot Amodal Video Object Segmentation—0
Textured Gaussians for Enhanced 3D Scene Appearance Modeling—0
MRI Breast tissue segmentation using nnU-Net for biomechanical modeling—0
Reconstructing Animals and the Wild—0
MARVEL-40M+: Multi-Level Visual Elaboration for High-Fidelity Text-to-3D Content CreationCode0
SelfSplat: Pose-Free and 3D Prior-Free Generalizable 3D Gaussian Splatting—0
Puzzle Similarity: A Perceptually-guided Cross-Reference Metric for Artifact Detection in 3D Scene Reconstructions—0
MVBoost: Boost 3D Reconstruction with Multi-View Refinement—0
Event-boosted Deformable 3D Gaussians for Dynamic Scene Reconstruction—0
PreF3R: Pose-Free Feed-Forward 3D Gaussian Splatting from Variable-length Image Sequence—0
An adversarial feature learning based semantic communication method for Human 3D Reconstruction—0
Semi-supervised Single-view 3D Reconstruction via Multi Shape Prior Fusion Strategy and Self-AttentionCode0
Open-World Amodal Appearance Completion—0
M3D: Dual-Stream Selective State Spaces and Depth-Driven Framework for High-Fidelity Single-View 3D ReconstructionCode0
Target Height Estimation Using a Single Acoustic Camera for Compensation in 2D Seabed Mosaicking—0
3D Reconstruction by Looking: Instantaneous Blind Spot Detector for Indoor SLAM through Mixed Reality—0
MTFusion: Reconstructing Any 3D Object from Single Image Using Multi-word Textual Inversion—0
Towards Degradation-Robust Reconstruction in Generalizable NeRF—0
BVI-CR: A Multi-View Human Dataset for Volumetric Video CompressionCode0
Poster: Reliable 3D Reconstruction for Ad-hoc Edge Implementations—0
DiHuR: Diffusion-Guided Generalizable Human Reconstruction—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