Sparse Feature Detection
Sparse Feature Detection is a feature detection method that identifies a minimal set of salient, non-redundant features in a signal or image by exploiting sparsity constraints to prioritize isolated or infrequent patterns over dense or uniformly distributed responses.
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5.7K
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356
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159
Institutions
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2017–2026
39
Parents
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Voting for Voting in Online Point Cloud Object Detection
Dominic Zeng Wang, Ingmar Posner · 2015 · 347 citations · Full text
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Chinese Academy of Sciences
Beijing, China
6 h-index
21 publications
467 citations
Tsinghua University
Beijing, China
5 h-index
13 publications
2K citations
University of Chinese Academy of Sciences
Beijing, China
4 h-index
10 publications
187 citations

Xi'an Jiaotong University
Xi'an, China
4 h-index
11 publications
438 citations
University of Michigan
Ann Arbor, United States
4 h-index
8 publications
396 citations

Northwestern Polytechnical University
Xi'an, China
2 h-index
5 publications
141 citations

University of Electronic Science and Technology of China
Chengdu, China
2 h-index
7 publications
794 citations
National University of Singapore
Singapore, Singapore
2 h-index
4 publications
94 citations
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TPAMI · 3 publications · 797 citations
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3 publications · 98 citations
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Repository · 3 publications · 62 citations
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MPE · 2 publications · 24 citations
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2 publications · 274 citations
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