Jay Xiong (jayxio)

jayxio

Geek Repo

Company:FamilyOfAIman

Location:USA

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Organizations
xuanwu-baidu

Jay Xiong's repositories

adCaptcha_test

The state-of-the-art adversary Captcha test framework

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AdvBox

Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.

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ChatDev

Create Customized Software using Natural Language Idea (through Multi-Agent Collaboration)

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cleverhans

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

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faceswap-GAN

A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.

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google-research

Google Research

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HaarCascadeCV

Detector that uses Viola-Jones algorithm on trained cascade to find head of hockey players

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Paddle

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)

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PaddleSleeve

PaddleSleeve

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LongLoRA

Code and documents of LongLoRA and LongAlpaca

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Micro8

Gitbook

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Mood-Helper_online

It's a online version of mood helper, written in JavaScript

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nslt

Neural Sign Language Translation (CVPR'18)

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Object_Detector_Deception

A tool-box for making physical object detector deception sticker

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PaddleDetection

Object detection and instance segmentation toolkit based on PaddlePaddle.

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PaddleRec

大规模推荐模型训练工具

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Real-Time-Voice-Cloning

Clone a voice in 5 seconds to generate arbitrary speech in real-time

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Sign-Language

A very simple CNN project.

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VehicleDrivingbehavior

Vehicle Behavior Detection based on Dashcam

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yobiface

Usage of https://github.com/davidsandberg/facenet/ model for people identification

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YOLO_attack

A demo for YOLO_attack

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YOLO_detector

YOLO object detector for experiment evaluation

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YOLO_detector-1

A YOLO detector to evaluation attack success rate.

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YOLO_tensorflow

tensorflow implementation of 'YOLO : Real-Time Object Detection'

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