… Recently, deep learning on point clouds has become even thriving, with … deep learning
methods for point clouds. It covers three major tasks, including 3D shape classification, 3D object …

… provides a general structure for learning with raw point clouds, and various methods … 3D
point cloud benchmark datasets and discusses the application of deep learning in popular 3D …

… point cloud. In this paper, the recent existing point cloud feature learning methods are classified
as point-… The former directly takes the raw point cloud as the input for deep learning. The …

… 3D scenes by fusing 2D images and 3D point clouds… deep Visual Geometry Group (VGG16)
is successfully created and fine-tuned by training seven deep convolutional neural networks …

… For point cloud sequences, points that are close spatially and temporally should be … In
this section, we first briefly review point cloud deep learning techniques. Then we describe the …

… faced by deep neural networks in processing massive, unstructured and noisy 3D points.
To demonstrate the latest progress of deep learning for 3D point cloud understanding, this …

… We introduce a simple permutation equivariant layer for deep learning with set structure. This
type … We use deep permutation-invariant networks to perform point-could classification and …

… of point cloud and downstream tasks, while the latest progress of deep learning in point cloud
… To stimulate the developments of point cloud completion in industry and academy, we con…

… the research interest in deep learning with 3D point clouds by showing that it is possible
to learn features of a point set with a special network that is robust to input point orders. This …

… We propose a new deep auto-encoder processing unorder point clouds data with lower …
We design a new deep learning-based method for sparse point clouds geometry compression. It …