Titlebook: Computer Vision – ACCV 2022; 16th Asian Conferenc Lei Wang,Juergen Gall,Rama Chellappa Conference proceedings 2023 The Editor(s) (if applic

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Social Aware Multi-modal Pedestrian Crossing Behavior Predictionnment. Previous methods ignored the inherent uncertainty of pedestrian future actions and the temporal correlations of spatial interactions. To solve the aforementioned problems, we propose a novel social aware multi-modal pedestrian crossing behavior prediction network. In this research field, our

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Christopher Patton,Thomas ShrimptonUnsupervised self-rehabilitation exercises and physical training can cause serious injuries if performed incorrectly. We introduce a learning-based framework that identifies the mistakes made by a user and proposes corrective measures for easier and safer individual training.

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https://doi.org/10.1007/978-3-031-26316-3computer vision; image processing; artificial intelligence; machine learning; image analysis; pattern rec

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978-3-031-26315-6The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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Computer Vision – ACCV 2022978-3-031-26316-3Series ISSN 0302-9743 Series E-ISSN 1611-3349

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