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 51–100 of 2326 papers

TitleStatusHype
BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown ObjectsCode3
Differentiable Voxel-based X-ray Rendering Improves Sparse-View 3D CBCT ReconstructionCode3
LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR SynthesisCode3
GES: Generalized Exponential Splatting for Efficient Radiance Field RenderingCode3
Geo4D: Leveraging Video Generators for Geometric 4D Scene ReconstructionCode3
Splatter Image: Ultra-Fast Single-View 3D ReconstructionCode3
SV3D: Novel Multi-view Synthesis and 3D Generation from a Single Image using Latent Video DiffusionCode3
Relaxing Accurate Initialization Constraint for 3D Gaussian SplattingCode3
SimpleRecon: 3D Reconstruction Without 3D ConvolutionsCode3
Kiss3DGen: Repurposing Image Diffusion Models for 3D Asset GenerationCode3
pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D ReconstructionCode3
Anything-3D: Towards Single-view Anything Reconstruction in the WildCode3
Point-NeRF: Point-based Neural Radiance FieldsCode3
PE3R: Perception-Efficient 3D ReconstructionCode3
EPRecon: An Efficient Framework for Real-Time Panoptic 3D Reconstruction from Monocular VideoCode3
PF3plat: Pose-Free Feed-Forward 3D Gaussian SplattingCode3
Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion TransformerCode3
DOGS: Distributed-Oriented Gaussian Splatting for Large-Scale 3D Reconstruction Via Gaussian ConsensusCode3
MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View StereoCode3
MUSt3R: Multi-view Network for Stereo 3D ReconstructionCode3
MVSplat360: Feed-Forward 360 Scene Synthesis from Sparse ViewsCode3
One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape OptimizationCode3
PanSplat: 4K Panorama Synthesis with Feed-Forward Gaussian SplattingCode3
Momentum-GS: Momentum Gaussian Self-Distillation for High-Quality Large Scene ReconstructionCode2
MicroDreamer: Efficient 3D Generation in 20 Seconds by Score-based Iterative ReconstructionCode2
MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface ReconstructionCode2
Memorize What Matters: Emergent Scene Decomposition from MultitraverseCode2
MegaLoc: One Retrieval to Place Them AllCode2
MicroDiffusion: Implicit Representation-Guided Diffusion for 3D Reconstruction from Limited 2D Microscopy ProjectionsCode2
MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian SplattingCode2
LuSNAR:A Lunar Segmentation, Navigation and Reconstruction Dataset based on Muti-sensor for Autonomous ExplorationCode2
LumiGauss: Relightable Gaussian Splatting in the WildCode2
MAC-Ego3D: Multi-Agent Gaussian Consensus for Real-Time Collaborative Ego-Motion and Photorealistic 3D ReconstructionCode2
3D Building Reconstruction from Monocular Remote Sensing Images with Multi-level SupervisionsCode2
LRM-Zero: Training Large Reconstruction Models with Synthesized DataCode2
Multiview Compressive Coding for 3D ReconstructionCode2
Learning Implicit Surface Light FieldsCode2
Learning Continuous Image Representation with Local Implicit Image FunctionCode2
PartGS:Learning Part-aware 3D Representations by Fusing 2D Gaussians and SuperquadricsCode2
LandMarkSystem Technical ReportCode2
CenterSnap: Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size EstimationCode2
Joint Reconstruction of 3D Human and Object via Contact-Based Refinement TransformerCode2
Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category ReconstructionCode2
InteractVLM: 3D Interaction Reasoning from 2D Foundational ModelsCode2
Kimera: from SLAM to Spatial Perception with 3D Dynamic Scene GraphsCode2
Local Feature Matching Using Deep Learning: A SurveyCode2
Multi-View Mesh Reconstruction with Neural Deferred ShadingCode2
HOLD: Category-agnostic 3D Reconstruction of Interacting Hands and Objects from VideoCode2
Boost 3D Reconstruction using Diffusion-based Monocular Camera CalibrationCode2
iHuman: Instant Animatable Digital Humans From Monocular VideosCode2
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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