Robust Feature Representation
Robust Feature Representation is a type of feature representation that maintains discriminative quality and structural consistency under variations, noise, and transformations in data, thereby enabling reliable performance across diverse and adverse conditions.
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2017–2026
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Speeded-Up Robust Features (SURF)
Herbert Bay, Andreas Ess, Tinne Tuytelaars et al. · Computer Vision and Image Understanding · 2008 · 13.4K citations
Alexandre Alahi, Pierre Vandergheynst · 2012 · 1.8K citations · Full text
Matthew D. Zeiler, Dilip Krishnan, Graham W. Taylor et al. · 2010 · 1.7K citations
Learning Deep Feature Representations with Domain Guided Dropout for Person Re-identification
Tong Xiao, Hongsheng Li, Wanli Ouyang et al. · 2016 · 985 citations
Deep Supervised Hashing for Fast Image Retrieval
Haomiao Liu, Ruiping Wang, Shiguang Shan et al. · 2016 · 929 citations
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Chinese Academy of Sciences
Beijing, China
33 h-index
161 publications
15.8K citations
University of Chinese Academy of Sciences
Beijing, China
19 h-index
81 publications
6.6K citations
Nanjing University of Science and Technology
Nanjing, China
18 h-index
49 publications
3.4K citations
Institute of Automation
Beijing, China
17 h-index
53 publications
5K citations
Wuhan University
Wuhan, China
17 h-index
62 publications
3.6K citations

Xidian University
Xi'an, China
16 h-index
63 publications
5.3K citations
Tsinghua University
Beijing, China
16 h-index
45 publications
2.4K citations
Nanyang Technological University
Singapore, Singapore
15 h-index
36 publications
1.6K citations
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Repository · 55 publications · 3.2K citations
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24 publications · 2.3K citations
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Conference · 23 publications · 1.9K citations
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25 publications · 1.3K citations
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