Few-shot Segmentation
Few-Shot Segmentation is a specialized image segmentation framework that enables the precise delineation of object regions in a target image by learning from a small set of annotated support examples, typically limited to one or few instances per object category.
209
Publications
15.3K
Citations
830
Authors
272
Institutions
Publications per year
2017–2026
209
Parents
209
PANet: Few-Shot Image Semantic Segmentation With Prototype Alignment
Kaixin Wang, Jun Hao Liew, Yingtian Zou et al. · 2019 · 1.4K citations
Chi Zhang, Guosheng Lin, Fayao Liu et al. · 2019 · 662 citations · Full text
Adaptive Prototype Learning and Allocation for Few-Shot Segmentation
Gen Li, Varun Jampani, Laura Sevilla-Lara et al. · 2021 · 426 citations
WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation
Jongheon Jeong, Taewan Kim, Dongqing Zhang et al. · 2023 · 363 citations
1–5 of 209
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272
University of Chinese Academy of Sciences
Beijing, China
14 h-index
35 publications
1.3K citations
Nanyang Technological University
Singapore, Singapore
12 h-index
34 publications
3.3K citations

Northwestern Polytechnical University
Xi'an, China
11 h-index
42 publications
4.7K citations

Northeastern University
Shenyang, China
7 h-index
29 publications
2.5K citations

Chinese Academy of Sciences
Beijing, China
7 h-index
23 publications
856 citations

South China University of Technology
Guangzhou, China
7 h-index
31 publications
1.3K citations
Tsinghua University
Beijing, China
6 h-index
10 publications
522 citations
Tencent (China)
Shenzhen, China
5 h-index
20 publications
708 citations
1–8 of 272
Repository · 31 publications · 1.2K citations
19
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9 publications · 629 citations
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Conference · 8 publications · 793 citations
8
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7 publications · 299 citations
7
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7 publications · 270 citations
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