Point Cloud Classification

99 papers with code • 2 benchmarks • 2 datasets

Point Cloud Classification is a task involving the classification of unordered 3D point sets (point clouds).


Use these libraries to find Point Cloud Classification models and implementations

Most implemented papers

Dynamic Graph CNN for Learning on Point Clouds

WangYueFt/dgcnn 24 Jan 2018

Point clouds provide a flexible geometric representation suitable for countless applications in computer graphics; they also comprise the raw output of most 3D data acquisition devices.

PCT: Point cloud transformer

MenghaoGuo/PCT 17 Dec 2020

It is inherently permutation invariant for processing a sequence of points, making it well-suited for point cloud learning.

Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks

MenghaoGuo/-EANet 5 May 2021

Attention mechanisms, especially self-attention, have played an increasingly important role in deep feature representation for visual tasks.

Deep Sets

lwtnn/lwtnn NeurIPS 2017

Our main theorem characterizes the permutation invariant functions and provides a family of functions to which any permutation invariant objective function must belong.

Relation-Shape Convolutional Neural Network for Point Cloud Analysis

Yochengliu/Relation-Shape-CNN CVPR 2019

Specifically, the convolutional weight for local point set is forced to learn a high-level relation expression from predefined geometric priors, between a sampled point from this point set and the others.

3D Point Cloud Classification and Segmentation using 3D Modified Fisher Vector Representation for Convolutional Neural Networks

sitzikbs/3DmFV-Net 22 Nov 2017

The point cloud is gaining prominence as a method for representing 3D shapes, but its irregular format poses a challenge for deep learning methods.

PointHop: An Explainable Machine Learning Method for Point Cloud Classification

minzhang-1/PointHop 30 Jul 2019

In the attribute building stage, we address the problem of unordered point cloud data using a space partitioning procedure and developing a robust descriptor that characterizes the relationship between a point and its one-hop neighbor in a PointHop unit.

Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds

hlei-ziyan/SPH3D-GCN 20 Sep 2019

We propose a spherical kernel for efficient graph convolution of 3D point clouds.

Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline

princeton-vl/SimpleView 9 Jun 2021

It also outperforms state-of-the-art methods on ScanObjectNN, a real-world point cloud benchmark, and demonstrates better cross-dataset generalization.

Benchmarking and Analyzing Point Cloud Classification under Corruptions

jiawei-ren/modelnetc 7 Feb 2022

3D perception, especially point cloud classification, has achieved substantial progress.