Learning Product Codebooks Using Vector-Quantized Autoencoders for Image Retrieval

Vector-Quantized Variational Autoencoders (VQ-VAE)[1] provide an unsupervised model for learning discrete representations by combining vector quantization and autoencoders. In this paper, we study the use of VQ-VAE for representation learning of downstream tasks, such as image retrieval. First, we d...

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Bibliographic Details

Published in:	2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) pp. 1 - 5
Main Authors:	Wu, Hanwei, Flierl, Markus
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.11.2019
Subjects:	Decoding Image coding Image reconstruction Image retrieval Training Vector quantization
Online Access:	Get full text
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