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

Showing 5175 of 2326 papers

TitleStatusHype
Hi3D: Pursuing High-Resolution Image-to-3D Generation with Video Diffusion ModelsCode3
EPRecon: An Efficient Framework for Real-Time Panoptic 3D Reconstruction from Monocular VideoCode3
Chat-Edit-3D: Interactive 3D Scene Editing via Text PromptsCode3
LaRa: Efficient Large-Baseline Radiance FieldsCode3
SpotlessSplats: Ignoring Distractors in 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
Lightplane: Highly-Scalable Components for Neural 3D FieldsCode3
LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR SynthesisCode3
LN3Diff: Scalable Latent Neural Fields Diffusion for Speedy 3D GenerationCode3
SV3D: Novel Multi-view Synthesis and 3D Generation from a Single Image using Latent Video DiffusionCode3
Relaxing Accurate Initialization Constraint for 3D Gaussian SplattingCode3
GES: Generalized Exponential Splatting for Efficient Radiance Field RenderingCode3
EscherNet: A Generative Model for Scalable View SynthesisCode3
pix2gestalt: Amodal Segmentation by Synthesizing WholesCode3
MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View StereoCode3
Splatter Image: Ultra-Fast Single-View 3D ReconstructionCode3
pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D ReconstructionCode3
One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape OptimizationCode3
Anything-3D: Towards Single-view Anything Reconstruction in the WildCode3
BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown ObjectsCode3
SimpleRecon: 3D Reconstruction Without 3D ConvolutionsCode3
Point-NeRF: Point-based Neural Radiance FieldsCode3
SIU3R: Simultaneous Scene Understanding and 3D Reconstruction Beyond Feature AlignmentCode2
Test3R: Learning to Reconstruct 3D at Test TimeCode2
Show:102550
← PrevPage 3 of 94Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
13D-R2N2Overall0.63Unverified
2GipumaOverall0.58Unverified
3COLMAPOverall0.53Unverified
4MVSNetOverall0.46Unverified
5Vis-MVSNetOverall0.37Unverified
6AA-RMVSNetOverall0.36Unverified
7Cas-MVSNetOverall0.36Unverified
8EPP-MVSNetOverall0.36Unverified
9PatchmatchNetOverall0.35Unverified
10CVP-MVSNetOverall0.35Unverified
#ModelMetricClaimedVerifiedStatus
1MD-GONIoU92.8Unverified
2POCOIoU92.6Unverified
3FS-SDFIoU91.2Unverified
4DP-ConvONetIoU89.5Unverified
5ConvONetIoU88.4Unverified
6ONetIoU76.1Unverified
7EVolTIoU73.8Unverified
8ZubicLioIoU65.43Unverified
#ModelMetricClaimedVerifiedStatus
1AttSets3DIoU0.64Unverified
2PSGN3DIoU0.64Unverified
3OGN3DIoU0.6Unverified
43D-R2N23DIoU0.56Unverified
#ModelMetricClaimedVerifiedStatus
1Scan2CADAverage Accuracy31.68Unverified
23DMatchAverage Accuracy10.29Unverified
#ModelMetricClaimedVerifiedStatus
1SVCPChamfer10Unverified
#ModelMetricClaimedVerifiedStatus
1EVLAccuracy18.2Unverified
#ModelMetricClaimedVerifiedStatus
1EVLAccuracy5.7Unverified
#ModelMetricClaimedVerifiedStatus
1Atlas (finetuned)3DIoU89.4Unverified