Open-set Image Retrieval

Open-Set Image Retrieval is an image retrieval paradigm that, unlike closed-set approaches, operates under the assumption that query images may contain object categories or instances not present in the training or gallery set, thereby requiring the system to handle unknown classes and reject out-of-distribution queries while retrieving relevant in-distribution matches.

6

Publications

212

Citations

27

Authors

11

Institutions

Publications per year

2017–2026

5

Authors

27

  1. NT
    Narges Tavakolpoursaleh

    1 publications · 11 citations

    1

    h-index

  2. JC
    Jianlong Chang

    Chinese Academy of Sciences, China

    1 publications · 27 citations

    1

    h-index

  3. YA
    Yannis Avrithis

    National Technical University of Athens, Greece

    1 publications · 92 citations

    1

    h-index

  4. PS
    Philipp Schaer

    TH Köln - University of Applied Sciences, Germany

    1 publications · 11 citations

    1

    h-index

  5. HL
    Haojie Li

    Dalian University of Technology, China

    1 publications · 27 citations

    1

    h-index

1–5 of 27

Venues

  1. 1

    h-index

  2. IEEE Robotics and Automation Letters

    1 publications · 10 citations

1–2