TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

Public facing notes page

A real-time approach for mapping all human pixels of 2D RGB images to a 3D surface-based model of the body

An adversarial example library for constructing attacks, building defenses, and benchmarking both

Taming Transformers for High-Resolution Image Synthesis

COCO API - Dataset @ http://cocodataset.org/

Efficient Image Captioning code in Torch, runs on GPU

Code repo for realtime multi-person pose estimation in CVPR'17 (Oral)

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller

Repository for benchmarking graph neural networks (JMLR 2023)

An interactive book on deep learning. Much easy, so MXNet. Wow. [Straight Dope is growing up] ---> Much of this content has been incorporated into the new Dive into Deep Learning Book available at …

Practical tutorials and labs for TensorFlow used by Nvidia, FFN, CNN, RNN, Kaggle, AE

Demo of running NNs across different frameworks

Automatic 2D-to-3D Video Conversion with CNNs

Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)

Various tutorials given for welcoming new students at MILA.

Code repository for Convolutional Pose Machines, CVPR'16

Data preparation and loader for AMASS

Keras version of Realtime Multi-Person Pose Estimation project

🌮 Trash Annotations in Context Dataset Toolkit

Attributing predictions made by the Inception network using the Integrated Gradients method

Detectorch - detectron for PyTorch

PyTorch Implementation for "TransPose: Keypoint localization via Transformer", ICCV 2021.

Code repo for "LSTM Pose Machines" (CVPR'18)

This repository contains the code to reproduce the core results from the paper "Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks".

w-net: a convolutional neural network architecture for the self-supervised learning of depthmap from pairs of stereo images.

Course "Theories of Deep Learning"

Pytorch Implementation of recent visual attribution methods for model interpretability