In the current digital information society, the personal authentication technique is an essential tool in many personal and enterprise security systems. Biometrics is an important personal authentication technique based on biological measurements, including physical, physiological, or behavioral characteristics. Compared with existing voice recognition, fingerprint scanning, and facial recognition, EEG-based biometrics has unique advantages (e.g., it is more difficult to be stolen, forged, or damaged, and it must be detected in vivo). Hence, EEG-based biometrics is capable of providing a more secure biometric method for identity recognition.
在当前的数字信息社会中，个人身份验证技术是许多个人和企业安全系统中必不可少的工具。生物特征识别是一种个人身份验证技术，使用生物测量，包括物理、生理或行为特征。有别于传统的指纹，声纹，脸部识别等身份识别方式，脑纹识别技术在不可窃取、不可伪造、不易受损、必须活体检测等方面具有独特的优势，能为身份识别提供更安全的生物识别方法，被称为最安全的下一代密码。

However, at present, EEG-based biometric technique is still in the exploratory stage. Current EEG-based biometric studies are mostly focused on a small number of samples and lack evaluation of multi-session and multi-task EEG recordings, which made the development of EEG-based biometric systems challenging with their uniqueness, permanence, and robustness. At the same time, there is no open EEG-based biometric competition and a suitable database. The lack of a unified test benchmark and platform seriously hinders the development of this field. To this end, we collected the M3CV (A Multi-subject, Multi-session, and Multi-task Database for Investigation of EEG Commonality and Variability) dataset and launched an EEG-based biometric competition.
然而，目前脑纹识别技术的发展仍处于探索阶段，存在数据样本量小、测试时段单一、记录范式单一等一系列局限性。同时，脑纹识别系统的准确性、稳定性和通用性受到挑战。同时，没有公开的基于脑电图的生物特征竞争。缺乏统一的测试基准和平台阻碍了这一领域的发展。为此，我们收集了M3CV（一个用于研究EEG共性和个性问题的多被试、多时间段和多任务的数据库）数据集，以启动基于脑电的脑纹识别竞争。

1 Qualified Participants参赛对象

1. This competition is open to the whole society, no age, status, nationality, related fields of individuals, colleges and universities, research institutions, enterprises, start-up teams, etc.
   本次竞赛面向全社会开放，不限年龄、身份、国籍，相关领域的个人、高等院校、科研机构、企业单位、初创团队等均可报名参赛。

2. Those who have access to the questions and dataset in advance are not allowed to participate in the competition. Other employees can participate in the ranking of the competition, but they are not allowed to receive any prizes.
   大赛主办单位中有机会提前接触赛题和数据的人员不得参加比赛，其他员工可以参与比赛排名，但不可领取任何奖项。

2 Requirement 参赛要求

1. We encourage participation by an individual or a team. Each team can have no more than 5 members, and can be formed across universities/institutions/enterprises freely, but each person can only join one team;
   支持以个人或团队形式参赛，每个参赛队伍人数最多不超过5人，允许跨单位自由组队，但每人只能参加一支队伍；

2. Contestants must ensure that the personal information provided is true, accurate and valid.
   参赛选手报名须保证所提供的个人信息真实、准确、有效。

3 Supplement 参赛须知补充

1. Fair competition: competitors are not allowed to copy others’ works, exchange answers or use more than one trumpet in the competition. If found guilty, the results will be cancelled and dealt with seriously.
   公平竞技： 参赛者禁止在比赛中抄袭他人作品、交换答案、使用多个小号，经发现将取消比赛成绩并严肃处理；

2. Organization statement: the organizing committee reserves the right to adjust and modify the rules of the competition, the arrangement of the competition, the right to judge and deal with cheating in the competition, and the right to withdraw or refuse awards to the participating teams that affect the organization and fairness.
   组织声明： 组委会保留对比赛规则、赛事安排进行调整和修改的权利、比赛作弊行为的判定权利和处置权利、收回或拒绝授予影响组织及公平性的参赛团队奖项的权利；

3. Baseline model: the baseline model is for the reference of competitors, and can be improved upon. Competitors cannot directly submit the prediction structure of the baseline model.
   基线模型： 基线模型供参赛选手参考，可以选择在其基础上改进。参赛选手不能直接提交基线模型的预测结构。

4. Property: The intellectual property rights of the entries (including but not limited to algorithms, models, etc.) belong to the contestants. The organizing committee has the right to use the entries and the team information related to the entries for promotional materials, relevant publications, designated and authorized media releases, official website browsing and downloading, exhibitions (including tour exhibitions) and other activities.
   作品产权： 参赛作品(包含但不限于算法、模型等)知识产权归参赛选手所有，组委会有权将参赛作品、以及作品相关的参赛团队信息用于宣传品、相关出版物、指定及授权媒体发布、官方网站浏览及下载、展览（含巡展）等活动项目。

4 Anti cheating instructions 反作弊说明

1. Participants are not allowed to register for multiple accounts. Once found, their scores will be cancelled and dealt with seriously.
   参与者禁止注册多账户报名，经发现将取消成绩并严肃处理；

2. Participants are not allowed to use rules loopholes or technical loopholes and other bad ways to improve their performance ranking outside the scope of technical ability assessment. Once found, their performance will be cancelled and dealt with seriously.
   参与者禁止在考核技术能力的范围外利用规则漏洞或技术漏洞等不良途径提高成绩排名，经发现将取消成绩并严肃处理；

3. or those who have access to relevant data of the competition, their submitted works will not be included in the rankings and awards；
   可以接触到赛题相关数据的人员，其提交作品将不计入排行榜及评奖；

4. AI Studio will collect player information, code, model and system report for performance evaluation, competition notice and other related competition matters.
   AI Studio将收集选手信息以及代码、模型、系统报告用于成绩评定、比赛通知等相关比赛事项。