A list of papers and datasets about point cloud analysis (processing)

GPT4Vis: What Can GPT-4 Do for Zero-shot Visual Recognition?

Official Code for ICML 2021 paper "Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline"

Code for the SIGGRAPH 2022 paper "DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds."

Linked Dynamic Graph CNN: Learning through Point Cloud by Linking Hierarchical Features

Code for "Rethinking the compositionality of point clouds through regularization in the hyperbolic space" (NeurIPS 2022)

Official code of paper "Efficient Joint Gradient Based Attack Against SOR Defense for 3D Point Cloud Classification" (MM'2020)

[ICRA 2023] ViPFormer: Efficient Vision-and-Pointcloud Transformer for Unsupervised Pointcloud Understanding.

[MMSP 2023, PCS 2024]

3D modeling of urban forests based on LiDAR point clouds

PyTorch implementation of SimpleView from "Revisiting Point Cloud Classification with a Simple and Effective Baseline", Goyal et al. (2020)

SE-PseudoGrid for the AutoCon journal paper.

Paper on 3D Point Cloud Processing

Implementation of point transformer for point cloud classification and segmentation

Directional PointNet: 3D Environmental Classification for Wearable Robots

This repository contains my paper reviews, solutions and code submissions for projects completed as part of CMSC848F during Fall 2023. Each project is organized in its own folder, with accompanying documentation and any necessary resources.

This repository refers to my master's thesis in the Data Science at Sapienza University. The objective is to build a model in order to perform the task of 3D fragment matching. Given two 3D scans of fragments, the model must predict whether they are adjacent or not.

Deep Learning based 3D Point Cloud Classification

DeepEMO: A Multi-Indicator Convolutional Neural Network-based Evolutionary Multi-Objective Algorithm

Point cloud classification demo in BinderHub