Official Code for ICML 2021 paper "Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline"
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Updated
Aug 20, 2023 - Python
Official Code for ICML 2021 paper "Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline"
A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
This is the official pytorch implementation for paper: IF-Defense: 3D Adversarial Point Cloud Defense via Implicit Function based Restoration
Dynamic Graph Convolutional Neural Network for 3D point cloud semantic segmentation
支持百度竞赛数据的中文事件抽取,支持ace2005数据的英文事件抽取,本人将苏神的三元组抽取算法中的DGCNN改成了事件抽取任务,并将karas改成了本人习惯使用的pytorch,在数据加载处考虑了各种语言的扩展
Dilate Gated Convolutional Neural Network For Machine Reading Comprehension
Attention-Based Temporal Learner With Dynamical Graph Neural Network for EEG Emotion Recognition. [DEAP]&&[MEEG]
Clean & Documented TF2 implementation of "An end-to-end deep learning architecture for graph classification" (M. Zhang et al., 2018).
Code and Data for the paper "LPF-Defense: 3D Adversarial Defense based on Frequency Analysis", PLoS ONE
PLEASE USE THE NEW REPO https://github.com/salehjg/DeepPoint-V2-FPGA . The deprecated in-order-queue-based repository for "DGCNN on FPGA: Acceleration of The Point CloudClassifier Using FPGAs".
Codes for the Point Cloud Analysis Project (IPL Lab, Sharif UT)
This repository contains the code to train a custom DGCNN segmentation model on 3D point cloud data and carry out post-processing to filter these point clouds from the k-regular graphs produced by the model.
This repository is a informal chainer version of the code implemented in https://github.com/WangYueFt/dgcnn.
Prototype of trackster tagging and smoothing for CMS HGCAL reconstructions at CERN.
Code for our article "Sparse Keypoint Segmentation of Lung Fissures: Efficient Geometric Deep Learning for Abstracting Volumetric Images"
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