Проект ML/DL определения сердечной недостаточности по векторной электрокардиографии

Myria3D: Aerial Lidar HD Semantic Segmentation with Deep Learning

Pytorch framework for doing deep learning on point clouds.

PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.

The official implementation code of Paper "PointCVaR: Risk-optimized Outlier Removal for Robust 3D Point Cloud Classification" in AAAI 2024 (Oral)

PointNet & ShapeNet

Point Cloud Segmentation Using PointNet

Geometry to Parameter Mapping based on Neural Networks. Point Cloud Regression Problem

Multimodal alignment of images and point clouds on the Modelnet-40-C dataset

Implementation of PointNet

This project focuses on training robots to grasp everyday objects accurately. We gather a unique point cloud dataset using an iPhone's LiDAR and process it with Polycam. We develop a PointNet model from scratch to perform multi-class classification and part-segmentation, guiding the robot on where to grasp objects.

UC Berkeley Deep Learning Final Project

Autoencoder for Point Clouds

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

🏙 Final project developed for the UPC-AIDL postgraduate course.

A pytorch implementation of PointNet and PointNet++

Point cloud classification in PyTorch

PyTorch implementation of "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593

New distributional and shape attacks on neural networks that process 3D point cloud data.

Rede neural para determinação da atitude de satélites.