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Context-empowered Visual Attention Prediction in Pedestrian Scenarios
In this paper, we present Context-SalNET, a novel encoder-decoder architecture that explicitly addresses three key challenges of visual attention prediction in pedestrians: First, Context-SalNET explicitly models the context factors urgency and safety preference in the latent space of the encoder-decoder model.
Improving Natural Language Processing Tasks with Human Gaze-Guided Neural Attention
A lack of corpora has so far limited advances in integrating human gaze data as a supervisory signal in neural attention mechanisms for natural language processing(NLP).
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