Discrete matrix factorization hashing for cross-modal retrieval

[1]  Ling Shao,et al.  Supervised Matrix Factorization Hashing for Cross-Modal Retrieval , 2016, IEEE Transactions on Image Processing.

[2]  Bart Thomee,et al.  New trends and ideas in visual concept detection: the MIR flickr retrieval evaluation initiative , 2010, MIR '10.

[3]  Hanjiang Lai,et al.  Supervised Hashing for Image Retrieval via Image Representation Learning , 2014, AAAI.

[4]  Gang Hua,et al.  Supervised Matrix Factorization for Cross-Modality Hashing , 2016, IJCAI.

[5]  Nicu Sebe,et al.  A Survey on Learning to Hash , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Rongrong Ji,et al.  Supervised hashing with kernels , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[7]  Guiguang Ding,et al.  Latent semantic sparse hashing for cross-modal similarity search , 2014, SIGIR.

[8]  Dongqing Zhang,et al.  Large-Scale Supervised Multimodal Hashing with Semantic Correlation Maximization , 2014, AAAI.

[9]  Moses Charikar,et al.  Similarity estimation techniques from rounding algorithms , 2002, STOC '02.

[10]  Guiguang Ding,et al.  Collective Matrix Factorization Hashing for Multimodal Data , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[11]  Roger Levy,et al.  On the Role of Correlation and Abstraction in Cross-Modal Multimedia Retrieval , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Rongrong Ji,et al.  Cross-Modality Binary Code Learning via Fusion Similarity Hashing , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[13]  Nikos Paragios,et al.  Data fusion through cross-modality metric learning using similarity-sensitive hashing , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[14]  Xuelong Li,et al.  Learning Discriminative Binary Codes for Large-scale Cross-modal Retrieval , 2017, IEEE Transactions on Image Processing.

[15]  Wei Liu,et al.  Supervised Discrete Hashing , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[16]  Zi Huang,et al.  Inter-media hashing for large-scale retrieval from heterogeneous data sources , 2013, SIGMOD '13.

[17]  Kristen Grauman,et al.  Kernelized Locality-Sensitive Hashing , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  Devraj Mandal,et al.  Generalized Semantic Preserving Hashing for N-Label Cross-Modal Retrieval , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[19]  M. Slaney,et al.  Locality-Sensitive Hashing for Finding Nearest Neighbors [Lecture Notes] , 2008, IEEE Signal Processing Magazine.

[20]  Tat-Seng Chua,et al.  NUS-WIDE: a real-world web image database from National University of Singapore , 2009, CIVR '09.

[21]  Michael Isard,et al.  A Multi-View Embedding Space for Modeling Internet Images, Tags, and Their Semantics , 2012, International Journal of Computer Vision.

[22]  Geyong Min,et al.  Supervised Intra- and Inter-Modality Similarity Preserving Hashing for Cross-Modal Retrieval , 2018, IEEE Access.

[23]  David W. Jacobs,et al.  Generalized Multiview Analysis: A discriminative latent space , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[24]  John Shawe-Taylor,et al.  Canonical Correlation Analysis: An Overview with Application to Learning Methods , 2004, Neural Computation.

[25]  Jianmin Wang,et al.  Semantics-preserving hashing for cross-view retrieval , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[26]  An Li,et al.  Efficient cross-modal retrieval via flexible supervised collective matrix factorization hashing , 2018, Multimedia Tools and Applications.