Piotr Napieralski

Papers

Total Citations

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About

Piotr Napieralski is a researcher specializing in computational visual attention modeling, with a focus on saliency detection in dynamic visual media such as films. His work bridges cognitive neuroscience, computer science, and robotics, aiming to replicate how human vision prioritizes regions of interest in complex scenes. Napieralski’s major contributions include developing a saliency-based visual attention model that integrates face detection and motion cues—two critical factors in guiding gaze during movie viewing. His 2018 paper, "The visual attention saliency map for movie retrospection" (6 citations), and his 2017 foundational work, "A model of saliency-based visual attention for movie retrospection" (3 citations), together form a framework for predicting where viewers look, with applications in video compression, autonomous systems, and human-computer interaction. While his citation counts are modest, his research addresses a niche yet growing field, offering practical tools for retrospection and scene understanding. Napieralski’s work is notable for its interdisciplinary approach, combining psychophysical insights with algorithmic design, making it valuable for students and researchers exploring attention-driven computer vision and its real-world uses.