Saliency modelling for 2D and 360° visual data: deep learning models and performance evaluation

This thesis explores the field of visual attention modeling, focusing on saliency prediction for both 2D and 360° visual data. The research is grounded in integrating deep learning techniques with human fixation data, aiming to refine current methods and address existing approaches’ limitations. Key