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 1326–1350 of 2326 papers

TitleStatusHype
Noise-NeRF: Hide Information in Neural Radiance Fields using Trainable Noise—0
NoiseTrans: Point Cloud Denoising with Transformers—0
UAV Object Detection and Positioning in a Mining Industrial Metaverse with Custom Geo-Referenced Data—0
UAVs and Birds: Enhancing Short-Range Navigation through Budgerigar Flight Studies—0
3D Reconstruction of Interacting Multi-Person in Clothing from a Single Image—0
Normal-guided Detail-Preserving Neural Implicit Function for High-Fidelity 3D Surface Reconstruction—0
Normal-guided Garment UV Prediction for Human Re-texturing—0
Not all Views are Created Equal: Analyzing Viewpoint Instabilities in Vision Foundation Models—0
Novel Light Field Imaging Device with Enhanced Light Collection for Cold Atom Clouds—0
NPLMV-PS: Neural Point-Light Multi-View Photometric Stereo—0
N-QGN: Navigation Map from a Monocular Camera using Quadtree Generating Networks—0
NRMVS: Non-Rigid Multi-View Stereo—0
NSLF-OL: Online Learning of Neural Surface Light Fields alongside Real-time Incremental 3D Reconstruction—0
NTR-Gaussian: Nighttime Dynamic Thermal Reconstruction with 4D Gaussian Splatting Based on Thermodynamics—0
Nuvo: Neural UV Mapping for Unruly 3D Representations—0
UE4-NeRF:Neural Radiance Field for Real-Time Rendering of Large-Scale Scene—0
UFM: A Simple Path towards Unified Dense Correspondence with Flow—0
Object 3D Reconstruction based on Photometric Stereo and Inverted Rendering—0
What's Behind the Couch? Directed Ray Distance Functions (DRDF) for 3D Scene Reconstruction—0
ObjectFolder: A Dataset of Objects with Implicit Visual, Auditory, and Tactile Representations—0
Object Gaussian for Monocular 6D Pose Estimation from Sparse Views—0
Object Learning and Robust 3D Reconstruction—0
UltraGauss: Ultrafast Gaussian Reconstruction of 3D Ultrasound Volumes—0
Object Tracking by Reconstruction with View-Specific Discriminative Correlation Filters—0
Object Wake-up: 3D Object Rigging from a Single Image—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