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Found 9 papers, 1 papers with code
DiffGaze: A Diffusion Model for Continuous Gaze Sequence Generation on 360° Images
We present DiffGaze, a novel method for generating realistic and diverse continuous human gaze sequences on 360{\deg} images based on a conditional score-based denoising diffusion model.
Learning User Embeddings from Human Gaze for Personalised Saliency Prediction
At the core of our method is a Siamese convolutional neural encoder that learns the user embeddings by contrasting the image and personal saliency map pairs of different users.
SeFFeC: Semantic Facial Feature Control for Fine-grained Face Editing
To ensure that the desired feature measurement is changed towards the target value without altering uncorrelated features, we introduced a novel semantic face feature loss.
Int-HRL: Towards Intention-based Hierarchical Reinforcement Learning
We show that intentions of human players, i. e. the precursor of goal-oriented decisions, can be robustly predicted from eye gaze even for the long-horizon sparse rewards task of Montezuma's Revenge - one of the most challenging RL tasks in the Atari2600 game suite.
Neuro-Symbolic Visual Dialog
We propose Neuro-Symbolic Visual Dialog (NSVD) -the first method to combine deep learning and symbolic program execution for multi-round visually-grounded reasoning.
Scanpath Prediction on Information Visualisations
We propose Unified Model of Saliency and Scanpaths (UMSS) -- a model that learns to predict visual saliency and scanpaths (i. e. sequences of eye fixations) on information visualisations.
Neural Photofit: Gaze-based Mental Image Reconstruction
The encoder extracts image features and predicts a neural activation map for each face looked at by a human observer.
How far are we from quantifying visual attention in mobile HCI?
With an ever-increasing number of mobile devices competing for our attention, quantifying when, how often, or for how long users visually attend to their devices has emerged as a core challenge in mobile human-computer interaction.
Accurate and Robust Eye Contact Detection During Everyday Mobile Device Interactions
Moreover, we discuss how our method enables the calculation of additional attention metrics that, for the first time, enable researchers from different domains to study and quantify attention allocation during mobile interactions in the wild.
