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Recent advancements in large vision language models (VLMs) tailored for autonomous driving (AD) have shown strong scene understanding and reasoning capabilities, making them undeniable candidates for end-to-end driving systems.
Privacy in autonomous vehicles
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Microsoft coco captions: Data collection and evaluation server
Xinlei Chen, Hao Fang, Tsung-Yi Lin, Ramakrishna Vedantam, Saurabh Gupta, Piotr Dollár, and C Lawrence Zitnick · 2015
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Lisa Collingwood · 2017
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Connected cars: Privacy, security issues related to connected, automated vehicles
Federal Trade Commission · 2017
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Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rogriguez, and Krishna P Gummadi · 2017
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Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Christos Sakaridis, Dengxin Dai, and Luc Van Gool · 2018
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Vizwiz grand challenge: Answering visual questions from blind people
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Gqa: A new dataset for real-world visual reasoning and compositional question answering
Drew A Hudson and Christopher D Manning · 2019
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Nocaps: Novel object captioning at scale
Harsh Agrawal, Karan Desai, Yufei Wang, Xinlei Chen, Rishabh Jain, Mark Johnson, Dhruv Batra, Devi Parikh, Stefan Lee, and Peter Anderson · 2019
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Il Bae, Jaeyoung Moon, Junekyo Jhung, Ho Suk, Taewoo Kim, Hyungbin Park, Jaekwang Cha, Jinhyuk Kim, Dohyun Kim, and Shiho Kim · 2020
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What a driver wants: User preferences in semi-autonomous vehicle decision-making
So Yeon Park, Dylan James Moore, and David Sirkin · 2020
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nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
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Scalability in perception for autonomous driving: Waymo open dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, et al · 2020
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Marin Toromanoff, Emilie Wirbel, and Fabien Moutarde · 2020
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Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles
SAE International · 2021
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Dada: Driver attention prediction in driving accident scenarios
Jianwu Fang, Dingxin Yan, Jiahuan Qiao, Jianru Xue, and Hongkai Yu · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Towards personalized autonomous driving: An emotion preference style adaptation framework
Jiali Ling, Jialong Li, Kenji Tei, and Shinichi Honiden · 2021
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End-to-end urban driving by imitating a reinforcement learning coach
Zhejun Zhang, Alexander Liniger, Dengxin Dai, Fisher Yu, and Luc Van Gool · 2021
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Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
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Chulin Xie, Zhong Cao, Yunhui Long, Diange Yang, Ding Zhao, and Bo Li · 2022
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Alexey Kurakin, Ian J Goodfellow, and Samy Bengio · 2022
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Coopernaut: end-to-end driving with cooperative perception for networked vehicles
Jiaxun Cui, Hang Qiu, Dian Chen, Peter Stone, and Yuke Zhu · 2022
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