Title: Semantic based generative compression of images at extremely low bitrates

Authors: T. Bordin, T. Maugey

Abstract:

We propose a framework for image compression in which the fidelity criterion is replaced by a semantic and quality preservation objective. Encoding the image thus becomes a simple extraction of semantic enabling to reach drastic compression ratio. The decoding side is handled by a generative model relying on the diffusion process for the reconstruction of images. We first propose to describe the semantic using low resolution
segmentation maps as guide. We further improve the generation introducing colors map guidance without retraining the generative decoder. We show that it is possible to produce images of high visual quality with preserved semantic at extremely low bitrates when compared with classical codecs.

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Title: Towards digital sobriety: why improving the energy efficiency of video streaming is not enough

Author: T. Maugey

Abstract: IPCC conclusions are unequivocal: we must divide our greenhouse gas emissions by two before 2030 if we want to maintain the global warming below 1.5°C in 2100. Hence, it becomes urgent to aim sobriety. Contrary to what is often claimed, digital technologies must also target global emission reduction, as their impact on the climate is huge and exploding every year. Among these digital technologies greenhouse gas emissions, those related to video processing and streaming are ones of the biggest. At the same time, a lot of research effort is currently done to reduce the energy consumed by algorithms or infrastructure. In this paper, we demonstrate that, even though such research works are crucial, they are not sufficient to enable global emissions reductions. The conclusion is that we must collectively think of other complementary solutions.