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SkateboardAI: The coolest video action recognition for skateboarding (student abstract)

(SkateboardAI: Die coolste Aktionserkennung für Videos beim Skateboarden (Student Abstract) )

Impressed by the coolest skateboarding sports program from 2021 Tokyo Olympic Games, we are the first to curate the original real-world video datasets "SkateboardAI" in the wild, even self-design and implement diverse uni-modal and multi-modal video action recognition approaches to recognize different tricks accurately. For uni-modal methods, we separately apply (1)CNN and LSTM; (2)CNN and BiLSTM; (3)CNN and BiLSTM with effective attention mechanisms; (4)Transformer-based action recognition pipeline. Transferred to the multi-modal conditions, we investigated the two-stream Inflated-3D architecture on "SkateboardAI" datasets to compare its performance with uni-modal cases. In sum, our objective is developing an excellent AI sport referee for the coolest skateboarding competitions.
© Copyright 2025 Proceedings of the AAAI Conference on Artificial Intelligence. Alle Rechte vorbehalten.

Bibliographische Detailangaben
Schlagworte:
Notationen:technische Sportarten Naturwissenschaften und Technik
Tagging:künstliche Intelligenz
Veröffentlicht in:Proceedings of the AAAI Conference on Artificial Intelligence
Sprache:Englisch
Veröffentlicht: 2025
Online-Zugang:https://doi.org/10.1609/aaai.v37i13.26952
Jahrgang:37
Heft:13
Seiten:16184-16185
Dokumentenarten:Artikel
Level:hoch