Hierarchical Representations for Spatio-Temporal Visual Attention Modeling and Understanding

Miguel-Ángel Fernández-Torres

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arXiv · 2308.05189

Hierarchical Representations for Spatio-Temporal Visual Attention Modeling and Understanding

Miguel-Ángel Fernández-Torres

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Abstract

This PhD. Thesis concerns the study and development of hierarchical representations for spatio-temporal visual attention modeling and understanding in video sequences. More specifically, we propose two computational models for visual attention. First, we present a generative probabilistic model for context-aware visual attention modeling and understanding. Secondly, we develop a deep network architecture for visual attention modeling, which first estimates top-down spatio-temporal visual attention, and ultimately serves for modeling attention in the temporal domain.

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BibTeX RIS

Miguel-Ángel Fernández-Torres. 2023-08-09. Hierarchical Representations for Spatio-Temporal Visual Attention Modeling and Understanding. https://arxiv.org/abs/2308.05189

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