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 1–25 of 2326 papers

TitleStatusHype
TripoSR: Fast 3D Object Reconstruction from a Single ImageCode9
Grounding Image Matching in 3D with MASt3RCode7
MASt3R-SLAM: Real-Time Dense SLAM with 3D Reconstruction PriorsCode7
Instant Neural Graphics Primitives with a Multiresolution Hash EncodingCode6
ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View SynthesisCode5
Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward PassCode5
RealFusion: 360° Reconstruction of Any Object from a Single ImageCode5
Real3D-Portrait: One-shot Realistic 3D Talking Portrait SynthesisCode5
Structure-Aware Sparse-View X-ray 3D ReconstructionCode5
SLAM3R: Real-Time Dense Scene Reconstruction from Monocular RGB VideosCode5
PatchRefiner: Leveraging Synthetic Data for Real-Domain High-Resolution Monocular Metric Depth EstimationCode5
MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View ImagesCode5
Neural Fields in Robotics: A SurveyCode5
Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse AttentionCode5
3D Reconstruction with Spatial MemoryCode5
DUSt3R: Geometric 3D Vision Made EasyCode5
Infinite Photorealistic Worlds using Procedural GenerationCode5
Prompting Depth Anything for 4K Resolution Accurate Metric Depth EstimationCode5
InstantSplat: Sparse-view SfM-free Gaussian Splatting in SecondsCode5
TripoSG: High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow ModelsCode5
GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and GenerationCode4
Cameras as Rays: Pose Estimation via Ray DiffusionCode4
GIM: Learning Generalizable Image Matcher From Internet VideosCode4
Highly Accurate Dichotomous Image SegmentationCode4
NeRDi: Single-View NeRF Synthesis with Language-Guided Diffusion as General Image PriorsCode4
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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