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Qiyue Yin
Researcher at Chinese Academy of Sciences
Publications - Â 48
Citations - Â 901
Qiyue Yin is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Cluster analysis & Computer science. The author has an hindex of 11, co-authored 34 publications receiving 654 citations. Previous affiliations of Qiyue Yin include Harbin Engineering University.
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A Comprehensive Survey on Cross-modal Retrieval
TL;DR: A number of representative methods for cross-modal retrieval are reviewed and classify them into two main groups: 1) real-valued representation learning, and 2) binary representation learning.
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Multi-view clustering via pairwise sparse subspace representation
TL;DR: A novel pairwise sparse subspace representation model for multi-view clustering is proposed and it is shown that the must-link and cannot-link constraints can be naturally integrated into the proposed model to obtain a link constrained multi-View clustering model.
Posted Content
Cross-modal Subspace Learning for Fine-grained Sketch-based Image Retrieval
Peng Xu,Qiyue Yin,Yongye Huang,Yi-Zhe Song,Zhanyu Ma,Liang Wang,Tao Xiang,W. Bastiaan Kleijn,Jun Guo +8 more
TL;DR: Through thorough examination of the experimental results, it is demonstrated that the subspace learning can effectively model the sketch-photo domain-gap, and a few key insights to drive future research are drawn.
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Cross-modal subspace learning for fine-grained sketch-based image retrieval
Peng Xu,Qiyue Yin,Yongye Huang,Yi-Zhe Song,Zhanyu Ma,Liang Wang,Tao Xiang,W. Bastiaan Kleijn,Jun Guo +8 more
TL;DR: In this article, a series of state-of-the-art cross-modal subspace learning methods are compared on two recently released fine-grained SBIR datasets.
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Unified subspace learning for incomplete and unlabeled multi-view data
Qiyue Yin,Shu Wu,Liang Wang +2 more
TL;DR: A novel subspace learning framework for incomplete and unlabeled multi-view data is proposed, which establishes a bridge for incomplete feature sets and an objective is developed along with an efficient optimization strategy.