Deep Event-Based Object Detection in Autonomous Driving: A Survey

Reliable Object detection plays a pivotal role in the realm of autonomous driving, requiring the precise and swift identification of objects within rapidly changing environments. Conventional frame-based cameras encounter difficulties in managing latency and bandwidth, highlighting the urgency for novel approaches. Event cameras have risen to prominence for their potential in autonomous vehicles, offering advantages such as minimal latency, extensive dynamic range, and reduced power usage. Nonetheless, harnessing the asynchronous and sparse nature of event data poses a challenge, especially when it comes to sustaining low-latency operations and creating efficient, lightweight detection frameworks. This paper offers a comprehensive review of object detection with event data for autonomous driving, highlighting the superior benefits that event cameras can provide.

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Publication Details

Published
2024-10-25
DOI
https://doi.org/10.1109/bigdia63733.2024.10808654
Citations
4
Primary Topic
Advanced Neural Network Applications
Type
article
Field-Weighted Citation Impact
1.00
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article

Deep Event-Based Object Detection in Autonomous Driving: A Survey

Yi Zhong, Jie Jiang, Bingquan Zhou, Tianjian Zhou
4 citations
Advanced Neural Network Applications
1.00
article

Deep Event-Based Object Detection in Autonomous Driving: A Survey

Yi Zhong, Jie Jiang, Bingquan Zhou, Tianjian Zhou
article en
4 citations

Abstract

Reliable Object detection plays a pivotal role in the realm of autonomous driving, requiring the precise and swift identification of objects within rapidly changing environments. Conventional frame-based cameras encounter difficulties in managing latency and bandwidth, highlighting the urgency for novel approaches. Event cameras have risen to prominence for their potential in autonomous vehicles, offering advantages such as minimal latency, extensive dynamic range, and reduced power usage. Nonetheless, harnessing the asynchronous and sparse nature of event data poses a challenge, especially when it comes to sustaining low-latency operations and creating efficient, lightweight detection frameworks. This paper offers a comprehensive review of object detection with event data for autonomous driving, highlighting the superior benefits that event cameras can provide.

National University of Defense Technology (CN)
Openalex Percentile: Top 21%
Advanced Neural Network Applications
1.00
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Deep Event-Based Object Detection in Autonomous Driving: A Survey — Yi Zhong, Jie Jiang, et al. · (2024) | TGRS Research Map | TGRS