Event-Based Eye Tracking AIS 2024 Challenge Survey
<|reference_start|>Event-Based Eye Tracking AIS 2024 Challenge Survey: 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.<|reference_end|>
@article{wang2024event-based,
    title={Event-Based Eye Tracking. AIS 2024 Challenge Survey},
    author={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 Br"uers, S'ebastien Crouzet, Douglas McLelland, Oliver Coenen,
  Baoheng Zhang, Yizhao Gao, Jingyuan Li, Hayden Kwok-Hay So, Philippe Bich,
  Chiara Boretti, Luciano Prono, Mircea Licu{a}, David Dinucu-Jianu,
  Cu{a}tu{a}lin Gr^iu, Xiaopeng Lin, Hongwei Ren, Bojun Cheng, Xinan Zhang,
  Valentin Vial, Anthony Yezzi, James Tsai},
    journal={arXiv preprint arXiv:2404.11770},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.11770},
    primaryClass={cs.CV cs.AI}
}