We propose a novel dictionary learning-based attention (\textit{Dic-Attn}) module, which models this issue as a decomposition and reconstruction problem.
The paper describes a novel attention module based on dictionary learning, which can be employed for several architectures in different computer vision tasks.
In this work, we propose a novel alternative dictionary learning-based attention (Dic-Attn) module, which models this issue as a decomposition and ...
Oct 23, 2023 · It provides an intuitive and elegant way to exploit the discriminative information from data and provides visual attention. The shallow-depth ...
May 30, 2024 · In this work, we propose a novel alternative dictionary learning-based attention (Dic-Attn) module, which models this issue as a decomposition ...
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Visual attention is a cognitive process that allows individuals to selectively focus on specific visual stimuli while filtering out irrelevant information.
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Mar 28, 2016 · In this work, we propose a novel top-down saliency model that jointly learns a Conditional Random Field (CRF) and a visual dictionary. The ...
Gomez and Snow (2017) found that object affordances guide overt attention during a visual search task; furthermore, the influence of affordances on attention is ...
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Visual attention helps achieve robust perception under noise, corruption, and distribution shifts in human vision, which are areas where modern.
Optimal Projections for Discriminative Dictionary Learning using the JL-lemma · Labeled projective dictionary pair learning: application to handwritten numbers ...