Gaze Estimation with an Ensemble of Four Architectures

• URL: http://arxiv.org/abs/2107.01980v1
• Date: Mon, 5 Jul 2021 12:40:26 GMT
• Title: Gaze Estimation with an Ensemble of Four Architectures
• Authors: Xin Cai, Boyu Chen, Jiabei Zeng, Jiajun Zhang, Yunjia Sun, Xiao Wang, Zhilong Ji, Xiao Liu, Xilin Chen, Shiguang Shan
• Abstract summary: We train several gaze estimators adopting four different network architectures. 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 $3.11circ$ on the ETH-XGaze test set.
• Score: 116.53389064096139
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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 $3.11^{\circ}$ on the ETH-XGaze test set.

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