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05_testinggrounds icon 05_testinggrounds

A Hunger-Games inspired FPS with large outdoor terrains. Advanced AI, basic networking, pickups, skeletal meshes, checkpoints and more. (ref: TG_URC) http://gdev.tv/urcgithub

2d-motion-retargeting icon 2d-motion-retargeting

PyTorch implementation for our paper Learning Character-Agnostic Motion for Motion Retargeting in 2D, SIGGRAPH 2019

6dpose icon 6dpose

implement some algorithms of 6d pose estimation

ai4animation icon ai4animation

Character Animation in Unity 3D using Deep Learning and Artificial Intelligence

aie_projects icon aie_projects

Projects done at the Academy of Interactive Entertainment

alphazero_gomoku icon alphazero_gomoku

An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)

als-community icon als-community

Replicated and optimized community version of Advanced Locomotion System V4 for Unreal Engine 4.26 with additional bug fixes.

arm9-compatible-soft-cpu-core icon arm9-compatible-soft-cpu-core

This ARMv4-compatible CPU core is written in synthesiable verilog.It could launch uCLinux and Linux in MODELSIM. It has high Dhrystone benchmark value: 1.2 DMIPS/MHz. It could be utilized in your FPGA design as one submodule, if you master the interface of this .v file. This IP core is very compact. It is one .v file and has only less 1800 lines.

augmentedautoencoder icon augmentedautoencoder

Official Code: Implicit 3D Orientation Learning for 6D Object Detection from RGB Images

baiyanhuang icon baiyanhuang

Automatically exported from code.google.com/p/baiyanhuang

bcnc icon bcnc

GRBL CNC command sender, autoleveler and g-code editor

bgfx icon bgfx

Cross-platform, graphics API agnostic, "Bring Your Own Engine/Framework" style rendering library.

caffe_ocr icon caffe_ocr

主流ocr算法研究实验性的项目,目前实现了CNN+BLSTM+CTC架构

cdlab icon cdlab

Yet another repository for developing and benchmarking deep learning-based change detection methods.

cmvs-pmvs icon cmvs-pmvs

This software (CMVS) takes the output of a structure-from-motion (SfM) software as input, then decomposes the input images into a set of image clusters of managable size. An MVS software can be used to process each cluster independently and in parallel, where the union of reconstructions from all the clusters should not miss any details that can be otherwise obtained from the whole image set. CMVS should be used in conjunction with an SfM software Bundler and an MVS software PMVS2 (PMVS version 2).

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