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Learning to Hash With Optimized Anchor Embedding for Scalable Retrieval
2017
IEEE Transactions on Image Processing
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Sparse representation and image hashing are 1 powerful tools for data representation and image retrieval respec-2 tively. ...
The combinations of these two tools for scalable image 3 retrieval, i.e., sparse hashing (SH) methods, have been proposed 4 in recent years and the preliminary results are promising. ...
, we proposed a novel Sparse Hashing method, 640 namely SHODE, for scalable retrieval. ...
doi:10.1109/tip.2017.2652730
pmid:28092559
fatcat:fadjluci5fcuniqrmjpcnkw4kq
Guest Editors' Introduction to the Special Section on Learning with Shared Information for Computer Vision and Multimedia Analysis
2018
IEEE Transactions on Pattern Analysis and Machine Intelligence
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The paper "Hetero-manifold Regularisation for Crossmodal Hashing" by F. Zheng, Y. Tang, and L. ...
The paper "Collaborative Index Embedding for Image Retrieval" by W. Zhou, H. Li, J. Sun, and Q. ...
doi:10.1109/tpami.2018.2804998
fatcat:urin3tvgy5f7ng5djfvlm4mop4
Guest editorial: web multimedia semantic inference using multi-cues
2015
World wide web (Bussum)
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A multi-modal semantic graph is constructed to find the embedded manifold cross-media correlations. The proposed method shows good performance in cross-media retrieval for image-audio dataset. ...
The correlations provide abundant context information for web multimedia semantic analysis. ...
doi:10.1007/s11280-015-0360-2
fatcat:vc4plge5qvg7hfmza3dffmawki
A Sparse Embedding and Least Variance Encoding Approach to Hashing
2014
IEEE Transactions on Image Processing
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Index Terms-hashing, manifold learning, image retrieval, dictionary learning. ...
This actually embeds each sample sparsely in the sample space. The sparse embedding vector is employed as the feature of each sample for hashing. ...
Linear spectral
Sparse
embedding
Least variance
encoding
Binarization
Sparse
embedding
0 0
0.28
0.11
0.61 0
(a) Joint learning of hash functions and binarization threshold
(b) Retrieval ...
doi:10.1109/tip.2014.2332764
pmid:24968174
fatcat:gpmxmttdkve4xefdnvrhqnf42a
Unsupervised Multi-modal Hashing for Cross-modal retrieval
[article]
2020
arXiv
pre-print
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In this paper, we propose a novel unsupervised hashing learning method to cope with this open problem to directly preserve the manifold structure by hashing. ...
Besides, the '2;1-norm constraint is imposed on the projection matrices to learn the discriminative hash function for each modality. ...
The sparse constraint is imposed on our model to learn discriminative hash functions for multimodal data. ...
arXiv:1904.00726v4
fatcat:6vupsinllvfh7ivzg2gozz7ffa
SDMCH: Supervised Discrete Manifold-Embedded Cross-Modal Hashing
2018
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
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To address these issues, in this paper, we present a novel cross-modal hashing method, named Supervised Discrete Manifold-Embedded Cross-Modal Hashing (SDMCH). ...
However, they neglect the fact that the high-dimensional data often exists on a low-dimensional manifold embedded in the ambient space and the relative proximity between the neighbors is also important ...
Related Work
Hashing with Manifold Learning Recent studies have demonstrated that it is beneficial for a retrieval model to exploit the non-linear manifold structure of multimedia data [Yang et al., ...
doi:10.24963/ijcai.2018/349
dblp:conf/ijcai/LuoYNSWX18
fatcat:v6embsbtu5akrp4ncn2tfezkkq
Hashing with Non-Linear Manifold Learning
2016
2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
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The amount of data is exploding with the development of Internet and multimedia technology. Rapid retrieval of mass data is becoming more and more important. ...
In this paper, we propose to use Isometric Mapping for dimensional reduction and utilize iterative quantization to reduce quantization loss during hashing process. ...
But for non-linear manifold such as Swiss Roll, further exploration is needed to catch the manifold structure in hash codes. ...
doi:10.1109/dicta.2016.7797046
dblp:conf/dicta/Liu0YWZ16
fatcat:ksvnur5ca5bd3p7ydhiidyeldy
The heterogeneous feature selection with structural sparsity for multimedia annotation and hashing: a survey
2012
International Journal of Multimedia Information Retrieval
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Furthermore, the effective utilization of intrinsic embedding structures in various features can boost the performance of multimedia retrieval. As a result, the appropriate This work was done when Z. ...
This paper introduces many of the recent efforts in sparsitybased heterogenous feature selection, the representation of the intrinsic latent structure embedded in multimedia, and the related hashing index ...
The feature selection and hashing of multimedia are the basis for image and video annotation and retrieval. ...
doi:10.1007/s13735-012-0001-9
fatcat:4ihorofn6zbg3mzqnifihgcydm
Graph PCA Hashing for Similarity Search
2017
IEEE transactions on multimedia
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Third, PCA is integrated with manifold learning to lean the hash functions using the probability representations of all representative data points. ...
of the big dataset; second, using the landmarks to generate a probability representation for each data point. ...
Both PCA and manifold based hashing methods achieve significant hashing performance, but are with inefficient retrieval speed, i.e., at least quadratic time complexity for the training stage. ...
doi:10.1109/tmm.2017.2703636
fatcat:ptlzaq75xjfcndtd6nmfcdb3ty
Hashing Cross-Modal Manifold for Scalable Sketch-Based 3D Model Retrieval
2014
2014 2nd International Conference on 3D Vision
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Experiments show that our proposed algorithm is more accurate and much faster than previous sketch-based 3D model retrieval algorithms. 3D shape retrieval; content-based multimedia retrieval; hashing; ...
The embedding is performed by a combination of spectral embedding and hashing into compact binary codes. ...
ACKNOWLEDGMENT This research is supported by JSPS Grant-in-Aid for Scientific Research on Innovative Areas #26120517 and JSPS Grants-in-Aid for Scientific Research (C) #26330133. ...
doi:10.1109/3dv.2014.72
dblp:conf/3dim/FuruyaO14
fatcat:xemh7wmb7fg5vj5askteke4zxm
Supervised Matrix Factorization Hashing for Cross-Modal Retrieval
2016
IEEE Transactions on Image Processing
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The target of cross-modal hashing is to embed heterogeneous multimedia data into a common low-dimensional Hamming space, which plays a pivotal part in multimedia retrieval due to the emergence of big multimodal ...
Index Terms-Cross-modal hashing, multimedia retrieval, collective matrix factorization, label consistency, local geometric consistency. Jun Tang is currently a Professor with the ...
INTRODUCTION ITH the explosive growth of multimedia data, it is of particular interest to develop algorithms for scalable retrieval of similar visual content in large-scale datasets. ...
doi:10.1109/tip.2016.2564638
pmid:27168597
fatcat:ihinkjn3hraj7hljppsqci7pja
Zero-Shot Hashing via Transferring Supervised Knowledge
[article]
2016
arXiv
pre-print
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Hashing has shown its efficiency and effectiveness in facilitating large-scale multimedia applications. ...
Extensive experiments conducted on various real-life datasets show the superior zero-shot image retrieval performance of ZSH as compared to several state-of-the-art hashing methods. ...
INTRODUCTION Hashing [30] is a powerful indexing technique for enabling efficient retrieval on large-scale multimedia data, such as image [25, 24, 38] and video [1] . ...
arXiv:1606.05032v1
fatcat:prm5zg5hrveedaizb466hq5kqu
Maximum Variance Hashing via Column Generation
2013
Mathematical Problems in Engineering
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With the explosive growth of the data volume in modern applications such as web search and multimedia retrieval, hashing is becoming increasingly important for efficient nearest neighbor (similar item) ...
Recently, a number of data-dependent methods have been developed, reflecting the great potential of learning for hashing. ...
Introduction Nearest neighbor search is a fundamental problem in many applications concerned with information retrieval, including content-based multimedia retrieval [1] [2] [3] , object and scene recognition ...
doi:10.1155/2013/379718
fatcat:ztdc6jjmfnbtjpy2ftrw3cprky
Learning Decorrelated Hashing Codes for Multimodal Retrieval
[article]
2019
arXiv
pre-print
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2018 pre-print arXiv:1803.00682v1 fatcat:ponw3hlcercc7d63piq62edyjm
When the hashing code length becomes longer, the retrieval performance improvement becomes slower. In this paper, we propose a minimum correlation regularization (MCR) for multimodal hashing. ...
Hashing is expected to be an efficient solution, since it represents data as binary codes. As the bit-wise XOR operations can be fast handled, the retrieval time is greatly reduced. ...
INTRODUCTION Multimodal hashing which embeds data to binary codes is an efficient tool for retrieving heterogeneous but correlated multimedia data, such as image-text pairs in Facebook and video-tag pairs ...
arXiv:1803.00682v2
fatcat:rogmcujiu5hkhnkwgpqlepo2du
2020 Index IEEE Transactions on Multimedia Vol. 22
2020
IEEE transactions on multimedia
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., +, TMM Dec. 2020 3180-3195 Deep Manifold-to-Manifold Transforming Network for Skeleton-Based Action Recognition. ...
., +, TMM Aug. 2020 2061-2073 Efficient Supervised Discrete Multi-View Hashing for Large-Scale Multimedia Search. ...
Image watermarking Blind Watermarking for 3-D Printed Objects by Locally Modifying Layer Thickness. 2780 -2791 Low-Light Image Enhancement With Semi-Decoupled Decomposition. ...
doi:10.1109/tmm.2020.3047236
fatcat:llha6qbaandfvkhrzpe5gek6mq
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