Introducing UN Salient360! Benchmark: A platform for evaluating visual attention models for 360° contents

Abstract

Virtual Reality (VR) provides the users with new immersive media experiences, offering the possibility to freely explore 360° content. Understanding these new exploration behaviors is crucial for the development of efficient techniques for processing, coding, delivering and rendering omnidirectional content to offer the highest possible Quality of Experience (QoE). Progress has already been made on visual attention (VA) modeling for 360° content. In this paper we briefly review the current status of research on this topic that led us to propose a benchmarking platform for evaluating and comparing the performance of models for saliency and scanpath prediction for 360° content. This paper introduces the ‘UN Salient360! benchmark” platform featuring a dataset, a toolbox and a framework for evaluation of different class of models. This online platform can be found in httns://salient360.ls2n.fr/.