目标检测
计算机科学
领域(数学)
数据科学
人工智能
开放式研究
模式识别(心理学)
万维网
数学
纯数学
作者
Xinzhu Ma,Wanli Ouyang,Andrea Simonelli,Elisa Ricci
标识
DOI:10.1109/tpami.2023.3346386
摘要
3D object detection from images, one of the fundamental and challenging problems in autonomous driving, has received increasing attention from both industry and academia in recent years. Benefiting from the rapid development of deep learning technologies, image-based 3D detection has achieved remarkable progress. Particularly, more than 200 works have studied this problem from 2015 to 2021, encompassing a broad spectrum of theories, algorithms, and applications. However, to date no recent survey exists to collect and organize this knowledge. In this paper, we fill this gap in the literature and provide the first comprehensive survey of this novel and continuously growing research field, summarizing the most commonly used pipelines for image-based 3D detection and deeply analyzing each of their components. Additionally, we also propose two new taxonomies to organize the state-of-the-art methods into different categories, with the intent of providing a more systematic review of existing methods and facilitating fair comparisons with future works. In retrospect of what has been achieved so far, we also analyze the current challenges in the field and discuss future directions for image-based 3D detection research.
科研通智能强力驱动
Strongly Powered by AbleSci AI