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weipanbuaa's Projects

1024crawer icon 1024crawer

基于python的1024爬虫,可爬下1024的文章和图片放到当前目录上。

ailearning icon ailearning

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

attention-module icon attention-module

Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"

caffe icon caffe

Caffe: a fast open framework for deep learning.

cbam.pytorch icon cbam.pytorch

Non-official implement of Paper:CBAM: Convolutional Block Attention Module

cvpr2020 icon cvpr2020

cvpr2020/cvpr2019/cvpr2018/cvpr2017 papers,极市团队整理

dcpdn icon dcpdn

Densely Connected Pyramid Dehazing Network (CVPR'2018)

doubledip icon doubledip

Official implementation of the paper "Double-DIP: Unsupervised Image Decomposition via Coupled Deep-Image-Priors"

funie-gan icon funie-gan

Fast underwater image enhancement using GANs. TensorFlow Implementation of FUnIE-GAN and UGAN.

gnnpapers icon gnnpapers

Must-read papers on graph neural networks (GNN)

keras-gan icon keras-gan

Keras implementations of Generative Adversarial Networks.

leetcodeanimation icon leetcodeanimation

Demonstrate all the questions on LeetCode in the form of animation.(用动画的形式呈现解LeetCode题目的思路)

models icon models

Models and examples built with TensorFlow

nrlpapers icon nrlpapers

Must-read papers on network representation learning (NRL) / network embedding (NE)

obfuscated-gradients icon obfuscated-gradients

Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

one-pixel-attack-keras icon one-pixel-attack-keras

Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet

py-faster-rcnn icon py-faster-rcnn

Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version

pytorch-gan icon pytorch-gan

PyTorch implementations of Generative Adversarial Networks.

pytorch-handbook icon pytorch-handbook

pytorch handbook是一本开源的书籍,目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门,其中包含的Pytorch教程全部通过测试保证可以成功运行

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