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
Parents
6
Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking
Filip Radenović, Ahmet İşcen, Giorgos Tolias et al. · 2018 · 92 citations · Full text
Open-Set Fine-Grained Retrieval via Prompting Vision-Language Evaluator
Shijie Wang, Jianlong Chang, Haojie Li et al. · 2023 · 27 citations
Open Set Logo Detection and Retrieval
Andras Tüzkö, Christian Herrmann, Daniel Manger et al. · 2018 · 19 citations · Full text
1–5 of 6
27
1 publications · 11 citations
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1
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1
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1–5 of 27
11

Vision Australia
Melbourne, Australia
1 h-index
1 publications
27 citations
Shandong University of Science and Technology
Qingdao, China
1 h-index
1 publications
27 citations
Commissariat à l'Énergie Atomique et aux Énergies Alternatives
Paris, France
1 h-index
3 publications
84 citations
Dalian University of Technology
Dalian, China
1 h-index
3 publications
81 citations
Huawei Technologies (China)
Shenzhen, China
1 h-index
2 publications
54 citations
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation
Karlsruhe, Germany
1 h-index
4 publications
76 citations
Karlsruhe Institute of Technology
Karlsruhe, Germany
1 h-index
2 publications
38 citations

The University of Sydney
Sydney, Australia
1 h-index
1 publications
27 citations
1–8 of 11
Conference · 1 publications · 35 citations
1
h-index
1 publications · 10 citations
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