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Where Is My Mind (looking at)? Predicting Visual Attention from Brain Activity

arXiv 2201.03902 ↗First posted 11 Jan 2022cs.CV cs.AI eess.SPcited by 0

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Abstract (arXiv)

Visual attention estimation is an active field of research at the crossroads of different disciplines: computer vision, artificial intelligence and medicine. One of the most common approaches to estimate a saliency map representing attention is based on the observed images. In this paper, we show that visual attention can be retrieved from EEG acquisition. The results are comparable to traditional predictions from observed images, which is of great interest. For this purpose, a set of signals has been recorded and different models have been developed to study the relationship between visual attention and brain activity. The results are encouraging and comparable with other approaches estimating attention with other modalities. The codes and dataset considered in this paper have been made available at urlhttps://figshare.com/s/3e353bd1c621962888ad to promote research in the field.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 13 of its 27 references that are in the map. First posted on arXiv 11 Jan 2022.

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References · 13

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2013Auto-Encoding Variational Bayescited by 4,053
  3. 2016EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfacescited by 628
  4. 2016NIPS 2016 Tutorial: Generative Adversarial Networkscited by 285
  5. 2016What do different evaluation metrics tell us about saliency models?cited by 185
  6. 2019EEG-Based Emotion Recognition Using Regularized Graph Neural Networkscited by 97
  7. 2020Unified Image and Video Saliency Modelingcited by 75
  8. 2017SalGAN: Visual Saliency Prediction with Generative Adversarial Networkscited by 65
  9. 2015Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networkscited by 45
  10. 2019Contextual Encoder-Decoder Network for Visual Saliency Predictioncited by 44
  11. 2019A Novel Bi-hemispheric Discrepancy Model for EEG Emotion Recognitioncited by 42
  12. 2016A Multimodal Approach to Estimating Vigilance Using EEG and Forehead EOGcited by 33
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  1. 2018Multi-channel EEG recordings during a sustained-attention driving taskcited by 32

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