QoMEX 2020 May 26th - 28th, Athlone, Ireland

Understanding the Quality of Experience (QoE) for visual media has been very important for optimal compression and content delivery for diverse video formats, and it has been a hot topic of research for the last decades. Researchers mostly studied this problem from a signal processing perspective using image and video processing tools, while learning-based methods have been increasing momentum recently. The popularisation of deep learning-based methods affected the whole signal and image processing community as a disruptive force, and visual QoE estimation is no different than others. Use of learning-based methods and especially deep learning methods open a new path for understanding the human visual system in the perception process and other QoE parameters. The objectives of this special session are twofold: first, to develop new metrics reaching beyond the performance of the legacy signal processing approaches for visual QoE estimation, and second, to understand the stages of human perception for visual media better utilising the learning-based methods and different analysis methods such as ablation studies.