This is the official codes for the paper "In the Eye of Transformer: Global-Local Correlation for Egocentric Gaze Estimation". (Project Page | paper)
Please find installation instructions in INSTALL.md. This repository is built based on SlowFast, so you can also refer to the instructions in SlowFast Installation. You may follow the instructions in DATASET.md to prepare the datasets. Pretrained models on Kinetics can be downloaded here.
Follow the example in GETTING_STARTED.md to start training your own model.
We have released our pretrained GLC model with best performance on EGTEA and Ego4D. You can download via these links [EGTEA weights | Ego4D weights].
If you find our work useful in your research, please use the following BibTeX entry for citation.
@article{lai2022eye,
title={In the Eye of Transformer: Global-Local Correlation for Egocentric Gaze Estimation},
author={Lai, Bolin and Liu, Miao and Ryan, Fiona and Rehg, James},
journal={British Machine Vision Conference},
year={2022}
}