Name: Matt De Vries
Type: User
Company: Institute of Cancer Research and Imperial College London
Bio: PhD candidate at the Institute of Cancer Research and Imperial College London. Working on geometric deep learning applied to cancer biology.
Twitter: devriesmatt
Location: London
Blog: https://devriesmatt.github.io
Matt De Vries's Projects
3D U-Net model for volumetric semantic segmentation written in pytorch
Image-to-Image Translation in PyTorch
Open-source Library of Image Super-Resolution Models, Datasets, and Metrics for Benchmarking or Pretrained Use
PyTorch implementations of Generative Adversarial Networks.
PyTorch for Semantic Segmentation
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
Tunable U-Net implementation in PyTorch
Integrated Cell project implemented in pytorch
Implementations of recent research prototypes/demonstrations using MONAI.
Retina blood vessel segmentation with a convolutional neural network
Code release for ECCV 2022 paper "RFNet-4D: Joint Object Reconstruction and Flow Estimation from 4D Point Clouds"
A collection of loss functions for medical image segmentation
Python image segmentation plugin
SHAPR - An AI approach to predict 3D cell shapes from 2D microscopic images
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations by T. Chen et al.
spatial transformer for 3d point clouds
The implementation of StyleGAN on PyTorch 1.0.1
Swiple enables you to easily observe, understand, validate and improve the quality of your data
Source code for the paper "TearingNet: Point Cloud Autoencoder to Learn Topology-Friendly Representations"
Loading and handling microscopy data in blender
N-dimensional NumPy array tiling and merging with overlapping, padding and tapering
Variational Recurrent Autoencoder for timeseries clustering in pytorch
The official pytorch implementation of our paper "Is Space-Time Attention All You Need for Video Understanding?"