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arXiv · 2607.09827

TDSal: Task-Based Top-Down Saliency Prediction Model

Can Mizrakli·Tolga K. Capin
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Abstract

Visual saliency aims to predict the regions of an image most likely to attract human visual attention. While most saliency models assume free-viewing conditions, human attention is often shaped by explicit task goals. In this work, we address task-driven saliency prediction by proposing a model that conditions visual attention on natural-language task descriptions. The model produces task-dependent saliency maps that reflect how attention shifts under different viewing intents. Through quantitative and qualitative analysis, we show that incorporating explicit task semantics enables more faithful modeling of goal-directed visual attention.

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Can Mizrakli, Tolga K. Capin. 2026-07-10. TDSal: Task-Based Top-Down Saliency Prediction Model. https://arxiv.org/abs/2607.09827

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