Hierarchical Representations for Spatio-Temporal Visual Attention Modeling and Understanding

Miguel-Ángel Fernández-Torres
8/9/2023
cs.CVcs.AIcs.LG

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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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Cite this paper

@article{fernndeztorres2023hierarchical,
  title  = {Hierarchical Representations for Spatio-Temporal Visual Attention Modeling and Understanding},
  author = {Miguel-Ángel Fernández-Torres},
  year   = {2023},
  eprint = {2308.05189},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2308.05189v1}
}

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