Nisk.ai

Video distribution faces two major revolutions. The first one is due to the impact of AI technologies and in particular deep learning. New ways to represent images and video have been proposed by the scientific community and might impact how content is encoded, with very promising outputs in terms of coding efficiency (e.g. the tradeoff between data-rate reduction and rendered perceived quality). The second revolution is the environmental impact of media consumption, and more generally of ICT (Information and Communication Technologies), on the global carbon footprint. This relates not only to the profusion of content and of its wide distribution, but also to how this content is processed and consumed, including users’ behavior. The first revolution also has an impact on the second one due to the increased complexity of deep learning architectures compared to conventional coding schemas.

The objective of this project is to address those challenges by proposing new deep-based video representation formats and coding schemes, taking into account efficiency, complexity and sustainability. Both 2D and immersive video will be considered.