PyRetri: A PyTorch-based Library for Unsupervised Image Retrieval by Deep Convolutional Neural Networks

Autor:	Hu, Benyi, Song, Ren-Jie, Wei, Xiu-Shen, Yao, Yazhou, Hua, Xian-Sheng, Liu, Yuehu
Rok vydání:	2020
Předmět:	Computer Science - Information Retrieval Computer Science - Computer Vision and Pattern Recognition Computer Science - Machine Learning Computer Science - Multimedia
Druh dokumentu:	Working Paper
Popis:	Despite significant progress of applying deep learning methods to the field of content-based image retrieval, there has not been a software library that covers these methods in a unified manner. In order to fill this gap, we introduce PyRetri, an open source library for deep learning based unsupervised image retrieval. The library encapsulates the retrieval process in several stages and provides functionality that covers various prominent methods for each stage. The idea underlying its design is to provide a unified platform for deep learning based image retrieval research, with high usability and extensibility. To the best of our knowledge, this is the first open-source library for unsupervised image retrieval by deep learning. Comment: Accepted by ACM Multimedia Conference 2020. PyRetri is open-source and available at https://github.com/PyRetri/PyRetri
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2005.02154 Zobrazit plný text záznamu View this record from Arxiv