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996.icu

Repo for counting stars and contributing. Press F to pay respect to glorious developers.

a-large-scale-attribute-dataset-for-zero-shot-learning

The download link for the dataset LAD.

ai-challenger-2017-datasets-download

AI Challenger 2017 Datasets Download

ai-research-tools

:hammer:AI 方向好用的科研工具

ai_challenger_2017

AI Challenger, a platform for open datasets and programming competitions to artificial intelligence (AI) talents around the world.

ai_challenger_2017_download

algorithm_interview_notes-chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

autodl-projects

Automated deep learning algorithms implemented in PyTorch.

autograd-hacks

awesome-coreset-selection

Awesome coreset/core-set/subset/sample selection works.

awesome-knowledge-distillation

Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2019)。

awesome-zero-shot-learning

A curated list of papers, code and resources pertaining to zero shot learning

cafe

This is a method of dataset condensation, and it has been accepted by CVPR-2022.

caffe

Caffe: a fast open framework for deep learning.

cifar-10-cnn

Play deep learning with CIFAR datasets

cifar-zoo

PyTorch implementation of CNNs for CIFAR benchmark

continual-representation-learning-for-biometric-identification

Continual Representation Learning for Biometric Identification

dataset-distillation

Dataset Distillation

datasetcondensation

dc-vae

(CVPR 2021) DC-VAE: Dual Contradistinctive Generative Autoencoder

deep-fonts

Generate fonts using deep learning

deep-leakage-from-gradients

[NeurIPS 2019] Deep Leakage From Gradients https://arxiv.org/abs/1906.08935

deepcore

Code for coreset selection methods

deeplearning

深度学习入门教程&&优秀文章&&Deep Learning Tutorial

embarrassingly-simple-zsl

This repository contains the code for the real data experiments presented in our paper “An embarrassingly simple approach to zero-shot learning”, presented at ICML 2015.

embedding_zero-shot-learning

end-to-end-incremental-learning

Pytorch implementation of End-to-End Incremental Learning [2018 ECCV Castro]

faster_rcnn

Faster R-CNN

generative-model-for-image-generation

Repository contains code for artificial image generation using generative models, namely, Variational Autoencoders (VAE) and Generative Adversarial Networks (GAN).

image_-retrieval-

数字图像处理课的作业