• OpenCV

  • Referenced in 116 articles [sw11376]
  • models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce...
  • PointNet

  • Referenced in 43 articles [sw31209]
  • Sets for 3D Classification and Segmentation. Point cloud is an important type of geometric data ... neural network that directly consumes point clouds and well respects the permutation invariance of points...
  • Camera Calibration

  • Referenced in 53 articles [sw13537]
  • reconstruction, and 3-D point cloud processing. With machine learning based frameworks, you can train ... system design, the system toolbox supports fixed-point arithmetic and C-code generation...
  • Gudhi

  • Referenced in 38 articles [sw08777]
  • shape, sampled by a point cloud. A popular approach is to construct, at different scales ... simplicial complexes built on top of the points, and then compute the persistent homology...
  • SegMatch

  • Referenced in 35 articles [sw23291]
  • Shape Segmentation and Shape Matching from Point Cloud: SegMatch software can decompose a shape into...
  • PCL

  • Referenced in 15 articles [sw22770]
  • Point Cloud Library (or PCL) is a large scale, open project [1] for 2D/3D image ... point cloud processing. The PCL framework contains numerous state-of-the art algorithms including filtering ... outliers from noisy data, stitch 3D point clouds together, segment relevant parts of a scene ... geometric appearance, and create surfaces from point clouds and visualize them -- to name...
  • VoxelNet

  • Referenced in 9 articles [sw32558]
  • VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection. Accurate detection ... objects in 3D point clouds is a central problem in many applications, such as autonomous ... interface a highly sparse LiDAR point cloud with a region proposal network (RPN), most existing ... manual feature engineering for 3D point clouds and propose VoxelNet, a generic 3D detection network...
  • PointCNN

  • Referenced in 8 articles [sw32557]
  • general framework for feature learning from point clouds. The key to the success of CNNs ... densely in grids (e.g. images). However, point clouds are irregular and unordered, thus directly convolving ... typical CNNs to feature learning from point clouds, thus we call it PointCNN. Experiments show...
  • jPlex

  • Referenced in 11 articles [sw09851]
  • finite simplicial complexes, often generated from point cloud data. This is the third of four...
  • NormFet

  • Referenced in 6 articles [sw23292]
  • Normals and Feature Sizes from Noisy Point Clouds. NormFet software can take a point cloud ... sample points. The output is a point cloud equipped with normals and feature sizes that ... subset but sufficiently many of points which is alright for AMLS. Feature sizes are estimated...
  • nanoflann

  • Referenced in 10 articles [sw22685]
  • datasets with different topologies: R2, R3 (point clouds...
  • OctNet

  • Referenced in 10 articles [sw36665]
  • object classification, orientation estimation and point cloud labeling...
  • VoxNet

  • Referenced in 10 articles [sw36666]
  • efficiently dealing with large amounts of point cloud data. In this paper, we propose VoxNet...
  • SimBa

  • Referenced in 10 articles [sw28063]
  • collapse. In topological data analysis, a point cloud data P extracted from a metric space...
  • PLEX

  • Referenced in 8 articles [sw06483]
  • complexes, generated from real or synthetic point-cloud data. The library defines a new kind ... current version) supports both rational (ie floating point) and mod 2 calculations...
  • MESHFREE

  • Referenced in 8 articles [sw31132]
  • commercial solution that follows an innovative point cloud approach. This enables engineers to analyze their...
  • ShortLoop

  • Referenced in 5 articles [sw28353]
  • trivial loops from point cloud data/simplicial complexes that represent a shortest homology basis. The simplicial ... artifacts. If the input is a point cloud data sampled from a smooth manifold ... Loops in a Shortest Homology Basis from Point Data. ACM 26th Annual Symposium on Computational...
  • Semantic3D.net

  • Referenced in 3 articles [sw36654]
  • Semantic3D.net: A new Large-scale Point Cloud Classification Benchmark. This paper presents ... point cloud classification benchmark data set with over four billion manually labelled points, meant ... true breakthrough for 3D point cloud labelling tasks due to lack of training data. With ... data set consists of dense point clouds acquired with static terrestrial laser scanners. It contains...
  • KPConv

  • Referenced in 4 articles [sw39851]
  • KPConv: Flexible and Deformable Convolution for Point Clouds. We present Kernel Point Convolution (KPConv ... point convolution, i.e. that operates on point clouds without any intermediate representation. The convolution weights ... located in Euclidean space by kernel points, and applied to the input points close...