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3D Point Cloud Matching

5 papers with code · Computer Vision
Subtask of 3D

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Greatest papers with code

3D-CODED : 3D Correspondences by Deep Deformation

13 Jun 2018ThibaultGROUEIX/3D-CODED

By predicting this feature for a new shape, we implicitly predict correspondences between this shape and the template.

 SOTA for 3D Point Cloud Matching on Faust (using extra training data)

3D HUMAN POSE ESTIMATION 3D POINT CLOUD MATCHING 3D SURFACE GENERATION

The Perfect Match: 3D Point Cloud Matching with Smoothed Densities

CVPR 2019 zgojcic/3DSmoothNet

Our approach is sensor- and sceneagnostic because of SDV, LRF and learning highly descriptive features with fully convolutional layers.

3D POINT CLOUD MATCHING

Fully Convolutional Geometric Features

International Conference on Computer vision 2019 chrischoy/FCGF

Extracting geometric features from 3D scans or point clouds is the first step in applications such as registration, reconstruction, and tracking.

3D FEATURE MATCHING 3D POINT CLOUD MATCHING 3D SHAPE REPRESENTATION METRIC LEARNING

Robust Point Set Registration Using Gaussian Mixture Models

IEEE Transactions on Pattern Analysis and Machine Intelligence 2010 bing-jian/gmmreg

Then, the problem of point set registration is reformulated as the problem of aligning two Gaussian mixtures such that a statistical discrepancy measure between the two corresponding mixtures is minimized.

3D POINT CLOUD MATCHING POINT CLOUD REGISTRATION