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FIFAWC: a dataset with detailed annotation and rich semantics for group activity recognition

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Conclusion

In this letter, we propose the FIFAWC dataset for GAR, offering unique features compared to existing ones. FIFAWC is meticulously annotated with all included GAs per sample augmenting both practicality and challenge. Additionally, rich semantic descriptions provide extensive adaptability for various GA-related tasks.

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Acknowledgements

This work was partly supported by the Research Program of State Key Laboratory of Software Development Environment and the Fundamental Research Funds for the Central Universities.

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Authors and Affiliations

  1. State Key Laboratory of Software Development Environment, School of Computer Science and Engineering, Beihang University, Beijing, 100191, China

    Duoxuan Pei & Di Huang

  2. Intelligent Recognition and Image Processing Lab., School of Computer Science and Engineering, Beihang University, Beijing, 100191, China

    Yunhong Wang

Authors
  1. Duoxuan Pei
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  2. Di Huang
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  3. Yunhong Wang
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Corresponding author

Correspondence to Di Huang.

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Competing interests The authors declare that they have no competing interests or financial conflicts to disclose.

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Pei, D., Huang, D. & Wang, Y. FIFAWC: a dataset with detailed annotation and rich semantics for group activity recognition. Front. Comput. Sci. 18, 186351 (2024). https://doi.org/10.1007/s11704-024-40027-3

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  • DOI: https://doi.org/10.1007/s11704-024-40027-3