http://torch.ch

:man: Code for "Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression"

Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition.

This repository implements a demo of the networks described in "How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)" paper.

Recurrent Neural Network library for Torch7's nn

A language-agnostic interface to TensorBoard

ATen: A TENsor library for C++11

A series of machine learning tutorials for Torch7

Load Caffe networks in Torch7

Recurrent Highway Networks - Implementations for Tensorflow, Torch7, Theano and Brainstorm

Official Torch7 implementation of "V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map", CVPR 2018

Torch7 -> CoreML

Demos and tutorials around Torch7.

A CUDA backend for Torch7

A deep learning library for streamlining research and development using the Torch7 distribution.

2.86% and 15.85% on CIFAR-10 and CIFAR-100

InceptionV3, InceptionV4, Inception-Resnet pretrained models for Torch7 and PyTorch

Implementation of Variational Auto-Encoder in Torch7

Code for Kaggle-CIFAR10 competition. 5th place.

TH++, C++ interface to the torch7 TH library

Torch7: state-of-the-art machine learning algorithms

This code implements a demo of the Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resources paper by Adrian Bulat and Georgios Tzimiropoulos.

Torch7 for iOS.

Torch7 implementation of Grid LSTM as described here: http://arxiv.org/pdf/1507.01526v2.pdf

A Compositional Object-Based Approach to Learning Physical Dynamics

Torch7+OpenCV+ConvNets

Training code for the networks described in "How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)" paper.

Porting of Skip-Thoughts pretrained models from Theano to PyTorch & Torch7

Real time face alignment

Torch Implementation of NIPS'16 paper: Perspective Transformer Nets