Event-Based Eye Tracking. AIS 2024 Challenge Survey
Zuowen Wang
Chang Gao
Zongwei Wu
Marcos V. Conde
Radu Timofte
Shih-Chii Liu
Qinyu Chen
Zheng-jun Zha
Wei Zhai
Han Han
Bohao Liao
Yuliang Wu
Zengyu Wan
Zhong Wang
Yang Cao
Ganchao Tan
Jinze Chen
Yan Ru Pei
Sasskia Brüers
Sébastien Crouzet
Douglas McLelland
Oliver Coenen
Baoheng Zhang
Yizhao Gao
Jingyuan Li
Hayden Kwok-Hay So
Philippe Bich
Chiara Boretti
Luciano Prono
Mircea Licua
David Dinucu-Jianu
Cuatualin Griu
Xiaopeng Lin
Hong Ren
Bo-Xun Cheng
Xinan Zhang
Valentin Vial
Anthony Yezzi
James Tsai

Abstract
This survey reviews the AIS 2024 Event-Based Eye Tracking (EET) Challenge. The task of the challenge focuses on processing eye movement recorded with event cameras and predicting the pupil center of the eye. The challenge emphasizes efficient eye tracking with event cameras to achieve good task accuracy and efficiency trade-off. During the challenge period, 38 participants registered for the Kaggle competition, and 8 teams submitted a challenge factsheet. The novel and diverse methods from the submitted factsheets are reviewed and analyzed in this survey to advance future event-based eye tracking research.
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