APES: Audiovisual Person Search in Untrimmed Video

@article{Alcazar2021APESAP,
  title={APES: Audiovisual Person Search in Untrimmed Video},
  author={Juan Leon Alcazar and Long Mai and Federico Perazzi and Joon-Young Lee and Pablo Arbel{\'a}ez and Bernard Ghanem and Fabian Caba Heilbron},
  journal={2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2021},
  pages={1720-1729}
}
Humans are arguably one of the most important subjects in video streams, many real-world applications such as video summarization or video editing workflows often require the automatic search and retrieval of a person of interest. Despite tremendous efforts in the person re-identification and retrieval domains, few works have developed audiovisual search strategies. In this paper, we present the Audiovisual Person Search dataset (APES), a new dataset composed of untrimmed videos whose audio… Expand

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