Dense Feature Representation
Dense Feature Representation is a type of feature representation in which each feature vector is characterized by a high-dimensional, continuous, and typically non-sparse numerical encoding that captures rich, distributed patterns across the entire input space.
270
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371
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Publications per year
2017–2026
184
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270
An analysis of single-layer networks in unsupervised feature learning
Adam Coates, Andrew Y. Ng, Honglak Lee · 2011 · 2.5K citations
D2-Net: A Trainable CNN for Joint Description and Detection of Local Features
Mihai Dusmanu, Ignacio Rocco, Tomáš Pajdla et al. · 2019 · 1.1K citations
DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion
Chen Wang, Danfei Xu, Yuke Zhu et al. · 2019 · 1.1K citations
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371

Chinese Academy of Sciences
Beijing, China
12 h-index
37 publications
2.5K citations
Tsinghua University
Beijing, China
10 h-index
31 publications
3.5K citations
University of Chinese Academy of Sciences
Beijing, China
9 h-index
20 publications
1.3K citations
ETH Zurich
Zurich, Switzerland
7 h-index
27 publications
3.2K citations
Nanyang Technological University
Singapore, Singapore
7 h-index
14 publications
757 citations

Shanghai Jiao Tong University
Shanghai, China
7 h-index
19 publications
3.8K citations

University of Macau
Macao, Macao
6 h-index
11 publications
1K citations

Beihang University
Beijing, China
6 h-index
9 publications
980 citations
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Repository · 27 publications · 1.5K citations
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TPAMI · 9 publications · 4.6K citations
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7 publications · 457 citations
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7 publications · 404 citations
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6 publications · 693 citations
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