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ai-blocks

A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models!

airsim

Open source simulator based on Unreal Engine for autonomous vehicles from Microsoft AI & Research

awesome-graph-classification

A collection of important graph embedding, classification and representation learning papers with implementations.

awesome-tensorlayer

TensorLayer - A curated list of dedicated resources

awr

Implementation of advantage-weighted regression.

books

ROS学习相关电子书，目前收集了10本

bookshelf

:books: books

bundlefusion

[Siggraph 2017] BundleFusion: Real-time Globally Consistent 3D Reconstruction using Online Surface Re-integration

cardiackinematicsphantom

Code to simulate mid LV motion in an analytical phantom and generate corresponding DENSE data

codeparkshare

Python初学者（零基础学习Python、Python入门）书籍、视频、资料、社区推荐

control-and-system-book

textbook about control, robotics, system

dart

Dynamic Animation and Robotics Toolkit

deep-image-prior

Image restoration with neural networks but without learning.

deep-learning-with-tensorflow-book

深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

deep-photo-styletransfer

Code and data for paper "Deep Photo Style Transfer": https://arxiv.org/abs/1703.07511

deep-voice-conversion

Deep neural networks for voice conversion (voice style transfer) in Tensorflow

deeplearnjs

Hardware-accelerated deep learning // machine learning // NumPy library for the web.

deepmimic

Motion imitation with deep reinforcement learning.

deepvideoanalytics

A distributed visual search and visual data analytics platform.

demos

densefusion

"DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion" code repository

design

Design documentation for ROS 2.0 effort

dive-into-dl-tensorflow2.0

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现，项目已得到李沐老师的同意

draco

Draco is a library for compressing and decompressing 3D geometric meshes and point clouds. It is intended to improve the storage and transmission of 3D graphics.

dynamic-movement-primitives

Implementation of a framework developed by Prof. Stefan Schaal for motor control in humanoid robots

dynamic-movement-primitives-and-imitation-learning-robotics

Dynamic movement primitives (DMPs) are a method of trajectory control/planning from Stefan Schaal’s lab. Complex movements have long been thought to be composed of sets of primitive action ‘building blocks’ executed in sequence and \ or in parallel, and DMPs are a proposed mathematical formalization of these primitives. The difference between DMPs and previously proposed building blocks is that each DMP is a nonlinear dynamical system. The basic idea is that you take a dynamical system with well specified, stable behavior and add another term that makes it follow some interesting trajectory as it goes about its business. The DMP differential equations (Transformation System, Canonical System, Non-linear Function) realize a general way of generating point-to-point movements. Imitation learning using linear regression is performed to compute the weight factor W from a demonstrated trajectory dataset, given by a teacher. The quality of the imitation is evaluated by comparing the training data with the data generated by the DMP.

dynamicfusion

Implementation of Newcombe et al. CVPR 2015 DynamicFusion paper

elasticfusion

Real-time dense visual SLAM system

elasticreconstruction

3D reconstruction system to creating detailed scene geometry from range video.

endeffector_stability

Stability control for the end effector of a six-axis robot (an industrial manipulator or a parallel platform)