A Survey on Intermediate Fusion Methods for Collaborative Perception Categorized by Real World Challenges

arXiv:2404.16139v1 Announce Type: new
Abstract: This survey analyzes intermediate fusion methods in collaborative perception for autonomous driving, categorized by real-world challenges. We examine various methods, detailing their features and the evaluation metrics they employ. The focus is on addressing challenges like transmission efficiency, localization errors, communication disruptions, and heterogeneity. Moreover, we explore strategies to counter adversarial attacks and defenses, as well as approaches to adapt to domain shifts. The objective is to present an overview of how intermediate fusion methods …

abstract arxiv autonomous autonomous driving challenges collaborative communication cs.cv cs.ro driving efficiency errors evaluation evaluation metrics features focus fusion intermediate localization metrics perception survey type world