Event-Based Eye Tracking. AIS 2024 Challenge Survey

Zuowen Wang, Chang Gao, Zongwei Wu, Marcos V. Conde, Radu Timofte +34 more
4/17/2024
cs.CVcs.AI

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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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Cite this paper

@article{wang2024eventbased,
  title  = {Event-Based Eye Tracking. AIS 2024 Challenge Survey},
  author = {Zuowen Wang and Chang Gao and Zongwei Wu and Marcos V. Conde and Radu Timofte and Shih-Chii Liu and Qinyu Chen and Zheng-jun Zha and Wei Zhai and Han Han and Bohao Liao and Yuliang Wu and Zengyu Wan and Zhong Wang and Yang Cao and Ganchao Tan and Jinze Chen and Yan Ru Pei and Sasskia Brüers and Sébastien Crouzet and Douglas McLelland and Oliver Coenen and Baoheng Zhang and Yizhao Gao and Jingyuan Li and Hayden Kwok-Hay So and Philippe Bich and Chiara Boretti and Luciano Prono and Mircea Lică and David Dinucu-Jianu and Cătălin Grîu and Xiaopeng Lin and Hongwei Ren and Bojun Cheng and Xinan Zhang and Valentin Vial and Anthony Yezzi and James Tsai},
  year   = {2024},
  eprint = {2404.11770},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2404.11770v1}
}

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