Published June 10, 2024 | Version v1
Preprint Open

Multimodality in Media Retrieval

  • 1. ROR icon Centre for Research and Technology Hellas
  • 2. ROR icon Reykjavík University


The quest for retrieving relevant media for a given query is well-studied and has various applications. Modern publicly available media collections provide diverse modalities of the same objects, which can enhance search. Our research delves into enhancing media retrieval by effectively representing and querying multimodal data. In the retrieval methods' ranking procedure, we examine efficiency through techniques like approximate nearest neighbor (ANN) indexing and high-performance computing (HPC). Our method, MuseHash, is proposed for single media object retrieval and is applied to images and 3D objects, outperforming existing methods on diverse datasets. Moreover, it significantly reduces  execution times with ANN and HPC. Future plans include considering multimodality in the video retrieval domain.



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XRECO - XR mEdia eCOsystem 101070250
European Commission
ALLIES - AI-based framework for supporting micro (and small) HSPs on the report and removaL of onLIne tErroriSt content 101080090
European Commission