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Ties van Rozendaal

2 accepted papers

2021

Overfitting for Fun and Profit: Instance-Adaptive Data Compression

ICLR 2021poster

Neural data compression has been shown to outperform classical methods in terms of $RD$ performance, with results still improving rapidly. At a high level, neural compression is based on an autoencoder that tries to reconstruct the input instance from a (quantized) latent representation, coupled wit…

Cited by 47SourcePDFScholar
2019

Video Compression With Rate-Distortion Autoencoders

ICCV 2019poster

In this paper we present a a deep generative model for lossy video compression. We employ a model that consists of a 3D autoencoder with a discrete latent space and an autoregressive prior used for entropy coding. Both autoencoder and prior are trained jointly to minimize a rate-distortion loss, whi…

Cited by 274PDFScholar