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TDSal: Task-Based Top-Down Saliency Prediction Model

2026-07-10 11:47:55
Can Mizrakli, Tolga K. Capin
arXiv_CV
         
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.

Abstract (translated)

URL

https://arxiv.org/abs/2607.09827

PDF

https://arxiv.org/pdf/2607.09827.pdf

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