Visualizations for machine learning datasets

Efficient Image Captioning code in Torch, runs on GPU

Microsoft Quantum Development Kit Samples

Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)

InferSent sentence embeddings

Dense image captioning in Torch

Various tutorials given for welcoming new students at MILA.

D2-Net: A Trainable CNN for Joint Description and Detection of Local Features

Object Detection

Evaluation of the CNN design choices performance on ImageNet-2012.

Training Very Deep Neural Networks Without Skip-Connections

Feature Pyramid Networks for Object Detection

tutorial notebooks

MAttNet: Modular Attention Network for Referring Expression Comprehension

Seed, Expand, Constrain: Three Principles for Weakly-Supervised Image Segmentation

Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

Code for training py-faster-rcnn and py-R-FCN on multiple GPUs in caffe

code for py-R-FCN-multiGPU maintained by bupt-priv

Code release for Hu et al. Natural Language Object Retrieval, in CVPR, 2016

Implementation of Excitation Backprop in Caffe

Demo for CVPR 2017 paper

Factorization Machine for regression and classification

Faster-RCNN based on Densecap(deprecated)

Training Low-bits DNNs with Stochastic Quantization

Pytorch implementation of pyramidnet