Region-based Image Retrieval
Region-Based Image Retrieval is a method in image retrieval that identifies and analyzes distinct visual regions within images to enable content-based matching, differing from global feature approaches by focusing on localized spatial structures and their semantic attributes.
410
Publications
30K
Citations
1K
Authors
402
Institutions
Publications per year
2017–2026
61
410
Scalable Recognition with a Vocabulary Tree
D. Nistér, Henrik Stewénius · 2006 · 3.6K citations
A survey of content-based image retrieval with high-level semantics
Ying Liu, Dengsheng Zhang, Guojun Lu et al. · Pattern Recognition · 2006 · 1.7K citations
Lost in quantization: Improving particular object retrieval in large scale image databases
James Philbin, Ondřej Chum, Michael Isard et al. · 2008 · 1.5K citations
1–5 of 410
1K
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402
Microsoft Research Asia (China)
Beijing, China
15 h-index
30 publications
3.1K citations

Monash University
Melbourne, Australia
9 h-index
24 publications
6.3K citations
Tsinghua University
Beijing, China
7 h-index
17 publications
989 citations

Zhejiang University
Hangzhou, China
7 h-index
11 publications
398 citations
Yonsei University
Seoul, South Korea
6 h-index
14 publications
445 citations
Microsoft (United States)
Redmond, United States
6 h-index
9 publications
3.4K citations
Stanford University
Stanford, United States
6 h-index
10 publications
3.2K citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
6 h-index
11 publications
1.7K citations
1–8 of 402
15 publications · 522 citations
13
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17 publications · 596 citations
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10 publications · 393 citations
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10 publications · 2K citations
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9 publications · 2.2K citations
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