# Personality-Driven Gaze Animation with Conditional Generative Adversarial Networks

arXiv: https://arxiv.org/abs/2012.02224 · HTML: https://mlsanity.com/paper/2012.02224/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Nov 2020.

## Built on by (most cited first, 1 of 1)

- [Personality Perception in Human Videos Altered by Motion Transfer Networks](https://mlsanity.com/paper/2401.14733/) (2024)

## Abstract (arXiv)

We present a generative adversarial learning approach to synthesize gaze behavior of a given personality. We train the model using an existing data set that comprises eye-tracking data and personality traits of 42 participants performing an everyday task. Given the values of Big-Five personality traits (openness, conscientiousness, extroversion, agreeableness, and neuroticism), our model generates time series data consisting of gaze target, blinking times, and pupil dimensions. We use the generated data to synthesize the gaze motion of virtual agents on a game engine.