Keras reimplementation of "One pixel attack for fooling deep neural networks" using differential evolution on cifar10
Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch
Pytorch implementation of deep person re-identification approaches.
RTSeg: Real-time Semantic Segmentation Comparative Study
Keras implementation of RetinaNet object detection
Face Recognition Project on MXNet
Code and data for paper "Deep Painterly Harmonization"
Yet Another Darknet 2 Keras
Equivariant CNNs for the sphere and SO(3) implemented in PyTorch
Convolutional Neural Networks
Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported.
Stochastic Weight Averaging in PyTorch
A pytorch implementation of Paper "Improved Training of Wasserstein GANs"
Multimodal Unsupervised Image-to-Image Translation
Keras implementations of Generative Adversarial Networks.
A general-purpose neural model for efficient learning of entity embeddings for solving a wide variety of problems
Open source implementation of the PAAC algorithm presented in Efficient Parallel Methods for Deep Reinforcement Learning
A re-implementation of the video classification experiments in the paper Non-local Neural Networks in Caffe2
PyTorch implementation of a deep metric learning technique called "Magnet Loss" from Facebook AI Research (FAIR).
Progressive Growing of GANs for Improved Quality, Stability, and Variation
PyTorch implementation of the Quasi-Recurrent Neural Network - up to 16 times faster than NVIDIA's cuDNN LSTM
This project is a faster faster R-CNN implementation, aimed to accelerating the training of faster R-CNN object detection models
A TensorFlow Implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model
Fast, flexible and easy to use probabilistic modelling in Python.
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
Deep recommender models using PyTorch.
Openpose from CMU implemented using Tensorflow with Custom Architecture for fast inference.
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
Image-to-image translation using conditional adversarial nets