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Conference Paper
ROD2021 Challenge
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- Authors
- Yizhou Wang, Jenq-Neng Hwang, Gaoang Wang, Hui Liu, Kwang-Ju Kim, Hung-Min Hsu, Jiarui Cai, Haotian Zhang, Zhongyu Jiang, Renshu Gu
- Issue Date
- 2021-08
- Citation
- International Conference on Multimedia Retrieval (ICMR) 2021, pp.553-559
- Language
- English
- Type
- Conference Paper
- Abstract
- The Radar Object Detection 2021 (ROD2021) Challenge, held in the ACM International Conference on Multimedia Retrieval (ICMR) 2021, has been introduced to detect and classify objects purely using an FMCW radar for autonomous driving applications. As a robust sensor to all-weather conditions, radar has rich information hidden in the radio frequencies, which can potentially achieve object detection and classification. This insight will provide a new object perception solution for an autonomous vehicle even in adverse driving scenarios. The ROD2021 Challenge is the first public benchmark focusing on this topic, which attracts great attention and participation. There are more than 260 participants among 37 teams from more than 10 countries with different academic and industrial affiliations, contributing about 300 submissions in the first phase and 400 submissions in the second phase. The final performance is evaluated by average precision (AP). Results add strong value and a better understanding of the radar object detection task for the autonomous vehicle community.
- KSP Keywords
- Autonomous vehicle, Average Precision, Detection task, International conference, Multimedia Retrieval, Object detection, Object perception, Radio Frequency(RF), Robust sensor, Second phase, autonomous driving