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In recent years there have been remarkable advancements in autonomous driving.
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2021
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D. Hafner, T. Lillicrap, M. Norouzi, and J. Ba, “Mastering Atari with Discrete World Models,” in
2021
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2021
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2021
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2022
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J. Zhou and J. Beyerer, “Corner Cases in Data-Driven Automated Driving: Definitions, Properties and Solutions,” in
2023
Closest in time.
D. Bogdoll, J. Hendl, F. Schreyer, N. Gowda, M. Färber, and J. M. Zöllner, “Impact, Attention, Influence: Early Assessment of Autonomous Driving Datasets,” in
2023
Closest in time.
D. Bogdoll, S. Uhlemeyer, K. Kowol, and J. M. Zöllner, “Perception Datasets for Anomaly Detection in Autonomous Driving: A Survey,” in
2023
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A. Kendall. (2023) Frontiers in Embodied AI for Autonomous Driving. CVPR Workshop on End-to-End Autonomous Driving. [Online]. Available:
2023
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2023
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D. Hafner, J. Pasukonis, J. Ba, and T. Lillicrap, “Mastering Diverse Domains through World Models,”
2023
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WAYVE, “Introducing GAIA-1: A Cutting-Edge Generative AI Model for Autonomy,”
2023
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A. Elluswamy, “Foundation models for autonomy,”
2023
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F. Mütsch, H. Gremmelmaier, N. Becker, D. Bogdoll, M. R. Zofka, and J. M. Zöllner, “From model-based to data-driven simulation: Challenges and trends in autonomous driving,” in
2023
Closest in time.
N. Chakraborty, A. Hasan, S. Liu, T. Ji, W. Liang, D. L. McPherson, and K. Driggs-Campbell, “Structural Attention-Based Recurrent Variational Autoencoder for Highway Vehicle Anomaly Detection,” in
2023
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M. Grcić, J. Šarić, and S. Šegvić, “On advantages of mask-level recognition for outlier-aware segmentation,” in
2023
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