-
Czech Technical University in Prague
- Prague, Czechia
- https://dmytro.ai
- @ducha_aiki
Highlights
- Pro
Stars
An Open Source Machine Learning Framework for Everyone
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
A curated list of awesome computer vision resources
Turi Create simplifies the development of custom machine learning models.
Style transfer, deep learning, feature transform
A collaboration friendly studio for NeRFs
🐍 Geometric Computer Vision Library for Spatial AI
Image-to-image translation with conditional adversarial nets
A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports comp…
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
A simple tool to update bib entries with their official information (e.g., DBLP or the ACL anthology).
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
pySLAM is a Python-based Visual SLAM pipeline that supports monocular, stereo, and RGB-D cameras. It offers a wide range of modern local and global features, multiple loop-closing strategies, a vol…
a programming library with geometric algorithms
PyTorch pre-trained model for real-time interest point detection, description, and sparse tracking (https://arxiv.org/abs/1712.07629)
A Unified Framework for Surface Reconstruction
Implementation of recent Deep Learning papers
Interactive convnet features visualization for Keras
Python library for reading and writing image data
Train to 94% on CIFAR-10 in <6.3 seconds on a single A100. Or ~95.79% in ~110 seconds (or less!)
Distributed deep learning on Hadoop and Spark clusters.
A PyTorch port of the Neural 3D Mesh Renderer
Monocular Depth Estimation Toolbox based on MMSegmentation.
PyTorch implementation of Spatial Transformer Network (STN) with Thin Plate Spline (TPS)