Rate-distortion-perception theory extends Shannon's rate-distortion theory by introducing a
constraint on the perceptual quality of the output. The perception constraint complements the …

In the context of lossy compression, Blau\& Michaeli (2019) adopt a mathematical notion of
perceptual quality and define the information rate-distortion-perception function …

Recent advances in machine learning-aided lossy compression are incorporating
perceptual fidelity into the rate-distortion theory. In this paper, we study the rate-distortion …

We study the rate-distortion-perception (RDP) tradeoff for a memoryless source model in the
asymptotic limit of large block-lengths. Our perception measure is based on a divergence …

In image compression, with recent advances in generative modeling, the existence of a
trade-off between the rate and the perceptual quality has been brought to light, where the …

We design a randomized scalar quantization scheme, where the quantization error is
independent of the source and follows any given unimodal distribution (eg Gaussian …

This survey articles focuses on emerging connections between the fields of machine
learning and data compression. While fundamental limits of classical (lossy) data …

We study an extension of lossy compression where the reconstruction distribution is different
from the source distribution in order to account for distributional shift due to processing. We …

We study an extension of lossy compression where the reconstruction is subject to a
distribution constraint which can be different from the source distribution. We formulate our …

This paper studies the rate-distortion-perception (RDP) tradeoff for a Gaussian vector source
coding problem where the goal is to compress the multi-component source subject to …