Hi, Iām Pedro Gomes, researcher in graph neural networks for point clouds
pedro-dm-gomes Goto Github PK
Type: User
Company: UCL
Location: London
Type: User
Company: UCL
Location: London
Hi, Iām Pedro Gomes, researcher in graph neural networks for point clouds
Allan Lab website
Pytorch package to compute Chamfer distance between point sets (pointclouds).
Computes the Earth Mover's Distance between two distributions using Scipy
FLOT: Scene Flow Estimation by Learned Optimal Transport on Point Clouds
FlowNet3D: Learning Scene Flow in 3D Point Clouds (CVPR 2019)
Code accompanying the NeurIPS 2019 paper "GOT: An Optimal Transport framework for Graph comparison"
Tensorflow Implementation of Graph-RNN for mmW denoising
This repository contains the dataset of Human Bodies Dataset
This is a complete package of recent deep learning methods for 3D point clouds in pytorch (with pretrained models).
MeteorNet: Deep Learning on Dynamic 3D Point Cloud Sequences (ICCV 2019 Oral)
Dynamic point cloud processing for action recognition
MilliNoise: a millimeter-wave sparse point cloud dataset in indoor scenarios
Temporal Interpolation of Dynamic Point Clouds using Convolutional Neural Networks
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PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
TensorFlow implementation of PointRNN, PointGRU and PointLSTM.
PyTorch Wrapper for Earth-Mover-Distance (EMD) for 3D point cloud regression
Human Activity Recognition from Point Clouds Generated through a Millimeter-wave Radar
Differentiable Point Cloud Sampling (CVPR 2020 Oral)
š£ Object detection of abstract shapes with neural networks
A tensorflow implementation of the Sinkhorn Distance calculation
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