Learning Product Codebooks using Vector Quantized Autoencoders for Image Retrieval

12 Jul 2018Hanwei WuMarkus Flierl

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 for downstream tasks, such as image retrieval... (read more)

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