Point Cloud Classification

58 papers with code • 1 benchmarks • 1 datasets

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

Datasets


Most implemented papers

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.

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.

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.

Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs

mys007/ecc CVPR 2017

A number of problems can be formulated as prediction on graph-structured data.

Adversarial shape perturbations on 3D point clouds

Daniel-Liu-c0deb0t/Adversarial-point-perturbations-on-3D-objects 16 Aug 2019

The importance of training robust neural network grows as 3D data is increasingly utilized in deep learning for vision tasks in robotics, drone control, and autonomous driving.

Geometric Back-projection Network for Point Cloud Classification

ShiQiu0419/GBNet 28 Nov 2019

As the basic task of point cloud analysis, classification is fundamental but always challenging.

PointHop++: A Lightweight Learning Model on Point Sets for 3D Classification

minzhang-1/PointHop2 9 Feb 2020

The PointHop method was recently proposed by Zhang et al. for 3D point cloud classification with unsupervised feature extraction.

Revisiting Point Cloud Classification with a Simple and Effective Baseline

princeton-vl/SimpleView 1 Jan 2021

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