Gaze Estimation with an Ensemble of Four Architectures
Computer Vision and Pattern Recognition
2021-07-06 v1
Abstract
This paper presents a method for gaze estimation according to face images. We train several gaze estimators adopting four different network architectures, including an architecture designed for gaze estimation (i.e.,iTracker-MHSA) and three originally designed for general computer vision tasks(i.e., BoTNet, HRNet, ResNeSt). Then, we select the best six estimators and ensemble their predictions through a linear combination. The method ranks the first on the leader-board of ETH-XGaze Competition, achieving an average angular error of on the ETH-XGaze test set.
Cite
@article{arxiv.2107.01980,
title = {Gaze Estimation with an Ensemble of Four Architectures},
author = {Xin Cai and Boyu Chen and Jiabei Zeng and Jiajun Zhang and Yunjia Sun and Xiao Wang and Zhilong Ji and Xiao Liu and Xilin Chen and Shiguang Shan},
journal= {arXiv preprint arXiv:2107.01980},
year = {2021}
}