Learning Gaussian Representation for Eye Fixation Prediction

arXiv:2403.14821v1 Announce Type: new
Abstract: Existing eye fixation prediction methods perform the mapping from input images to the corresponding dense fixation maps generated from raw fixation points. However, due to the stochastic nature of human fixation, the generated dense fixation maps may be a less-than-ideal representation of human fixation. To provide a robust fixation model, we introduce Gaussian Representation for eye fixation modeling. Specifically, we propose to model the eye fixation map as a mixture of probability distributions, namely a …

abstract arxiv cs.cv generated however human images mapping maps nature prediction raw representation robust stochastic type