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fleetai

flownet3d

FlowNet3D: Learning Scene Flow in 3D Point Clouds

folly

An open-source C++ library developed and used at Facebook.

fuse

The fuse stack provides a general architecture for performing sensor fusion live on a robot. Some possible applications include state estimation, localization, mapping, and calibration.

g2o

g2o: A General Framework for Graph Optimization

gan_stability

Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"

gans-from-theory-to-production

Material for the tutorial: "Deep Diving into GANs: from theory to production"

garage

A framework for reproducible reinforcement learning research

gat

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

gcnv2_slam

Real-time SLAM system with deep features

generative-reversible

github-cheat-sheet

A list of cool features of Git and GitHub.

glow-pytorch

pytorch implementation of openai paper "Glow: Generative Flow with Invertible 1×1 Convolutions"

golang-100-days

Golang - 100天从新手到大师

golang-crawler

In progress, a distributed crawler written with Golang

gp-dip

Code for A Bayesian Perspective on the Deep Image Prior (CVPR 2019)

gpflow

Gaussian processes in TensorFlow

gpu_computing_in_robotics

grokking-pytorch

The Hitchiker's Guide to PyTorch

grpc

The C based gRPC (C++, Node.js, Python, Ruby, Objective-C, PHP, C#)

gslam

A General Simultaneous Localization and Mapping Framework which supports feature based or direct method and different sensors including monocular camera, RGB-D sensors or any other input types can be handled.

gym-gazebo

A toolkit for developing and comparing reinforcement learning algorithms using ROS and Gazebo.

gym-gazebo2

gym-gazebo2 is a toolkit for developing and comparing reinforcement learning algorithms using ROS 2 and Gazebo

gym-http-api

API to access OpenAI Gym from other languages via HTTP

handful-of-trials

Experiment code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"

hands-on-meta-learning-with-python

Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow

hdl_graph_slam

3D LIDAR-based Graph SLAM

home-platform

HoME: a Household Multimodal Environment is a platform for artificial agents to learn from vision, audio, semantics, physics, and interaction with objects and other agents, all within a realistic context.

hotdog-not-hotdog

Pytorch model recognizing hotdogs and not-hotdogs deployed on flask. Inspired by Sillicon Valley TV series.

how-to-learn-robotics

开源机器人学学习指南