Summary of Event-based Eye Tracking. Ais 2024 Challenge Survey, by Zuowen Wang et al.

Event-Based Eye Tracking. AIS 2024 Challenge Survey

by 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 Lică, David Dinucu-Jianu, Cătălin Grîu, Xiaopeng Lin, Hongwei Ren, Bojun Cheng, Xinan Zhang, Valentin Vial, Anthony Yezzi, James Tsai

First submitted to arxiv on: 17 Apr 2024

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Summary difficulty	Written by	Summary
High	Paper authors	High Difficulty Summary Read the original abstract here
Medium	GrooveSquid.com (original content)	Medium Difficulty Summary This paper reviews the AIS 2024 Event-Based Eye Tracking (EET) Challenge, which aimed to process eye movement recorded with event cameras and predict pupil center. The challenge prioritized efficient eye tracking with event cameras while achieving a good balance between task accuracy and efficiency. The survey analyzed the diverse methods used by 8 teams that submitted factsheets during the challenge period, aiming to advance future event-based eye tracking research.
Low	GrooveSquid.com (original content)	Low Difficulty Summary This paper looks at how computers can track people’s eyes using special cameras called “event cameras”. It’s like trying to guess where someone’s looking based on their eye movements. The goal is to do this quickly and accurately, which is important for things like helping people with disabilities or making video games more interactive. The paper talks about a competition where teams tried different ways to track eyes using event cameras and shares the results.