Back from New York! Seriously, West Point is Hogwarts:

Enabling delightful user experiences via predictive models of human attention

• In this blog, we present two papers (one from CVPR 2022, and one just accepted to CVPR 2023) that highlight our recent research in the area of human attention modeling: “Deep Saliency Prior for Reducing Visual Distraction” and “Learning from Unique Perspectives: User-aware Saliency Modeling”, together with recent research on saliency driven progressive loading for image compression (1, 2). We showcase how predictive models of human attention can enable delightful user experiences such as image editing to minimize visual clutter, distraction or artifacts, image compression for faster loading of webpages or apps, and guiding ML models towards more intuitive human-like interpretation and model performance. We focus on image editing and image compression, and discuss recent advances in modeling in the context of these applications.