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Continual learning in cross-modal retrieval
[article]
2021
arXiv
pre-print
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In this paper, we propose a combination of both problems into a continual cross-modal retrieval setting, where we study how the catastrophic interference caused by new tasks impacts the embedding spaces ...
and their cross-modal alignment required for effective retrieval. ...
Figure 3 . 3 Types of pairs in continual cross-modal retrieval: (a) available in joint training, and (b) available in continual learning, i.e. without cross-task negative pairs (CTNP). ...
arXiv:2104.06806v2
fatcat:qlgyuuxcnbhyjes5n36cm7kfym
Cross-Modal Hamming Hashing
[chapter]
2018
Lecture Notes in Computer Science
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Cross-modal hashing enables similarity retrieval across different content modalities, such as searching relevant images in response to text queries. ...
This work presents Cross-Modal Hamming Hashing (CMHH), a novel deep cross-modal hashing approach that generates compact and highly concentrated hash codes to enable efficient and effective Hamming space ...
This paper presents Cross-Modal Hamming Hashing (CMHH), a unified deep learning framework for cross-modal Hamming space retrieval, as shown in Fig. 2 . ...
doi:10.1007/978-3-030-01246-5_13
fatcat:42mkbkebrvfhrnmctbk5p65npu
Transitive Hashing Network for Heterogeneous Multimedia Retrieval
[article]
2016
arXiv
pre-print
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Cross-modal hashing enables efficient retrieval from database of one modality in response to a query of another modality. ...
Existing work on cross-modal hashing assumes heterogeneous relationship across modalities for hash function learning. ...
We use the mini-batch stochastic gradient descent (SGD) with 0.9 momentum and the learning rate strategy in Caffe, cross-validate learning rate from 10 −5 to 10 −1 with a multiplicative step-size 10 1/ ...
arXiv:1608.04307v1
fatcat:l2xakppke5b5vgwcgs7wwliufq
Correlation Hashing Network for Efficient Cross-Modal Retrieval
[article]
2017
arXiv
pre-print
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Extensive empirical study shows that CHN yields state of the art cross-modal retrieval performance on standard benchmarks. ...
Cross-modal hashing improves the quality of hash coding by exploiting semantic correlations across different modalities. ...
These results verify that CHN is able to learn high-quality hash codes for effective cross-modal retrieval. ...
arXiv:1602.06697v2
fatcat:wemcafkkojbvppdkclyj5knglq
Emotion Embedding Spaces for Matching Music to Stories
2021
Zenodo
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Our experiments show that by leveraging these embedding spaces, we are able to successfully bridge the gap between modalities to facilitate cross modal retrieval. ...
., books), use multiple sentences as input queries, and automatically retrieve matching music. We formalize this task as a cross-modal text-to-music retrieval problem. ...
cross-modal retrieval. ...
doi:10.5281/zenodo.5624482
fatcat:uqlm3s5korb5rm2ybkbvr42qpi
Sequential Learning for Cross-Modal Retrieval
2019
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)
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Inspired by the recent achievement in the field of cognition mechanism on how the human brain acquires knowledge, we propose a new sequential learning method for cross-modal retrieval. ...
Cross-modal retrieval has attracted increasing attention with the rapid growth of multimodal data, but its learning paradigm under changing environment is less studied. ...
Related Work Cross-modal retrieval. Cross-modal learning approaches [2, 9, 5, 19, 31, 16] can roughly be divided into continual-value learning method and hashing method. ...
doi:10.1109/iccvw.2019.00554
dblp:conf/iccvw/SongT19
fatcat:wq7czx7byvhsngmhhwzofsvde4
Modality-Dependent Cross-Modal Retrieval Based on Graph Regularization
2020
Mobile Information Systems
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In order to fully exploit the potential correlation of different modalities, we propose a cross-modal retrieval framework based on graph regularization and modality dependence (GRMD). ...
Nowadays, the heterogeneity gap of different modalities is the key problem for cross-modal retrieval. ...
cross-modal retrieval based on graph regularization in I2T. datasets. ...
doi:10.1155/2020/4164692
fatcat:2ku7xp5x65bkhggvu7x7skspja
A Cross-Media Retrieval Method Based on Semisupervised Learning and Alternate Optimization
2021
Mobile Information Systems
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The most difficult task for cross-media retrieval lies in the potential correlation between different modalities data and how to overcome the semantic gap. ...
This paper proposes a cross-media retrieval method based on semisupervised learning and alternate optimization (SMDCR) to overcome the abovementioned difficulties, thereby improving the retrieval accuracy ...
modalities data in cross-media retrieval. ...
doi:10.1155/2021/9947644
doaj:90a40b8f33a34c6fa8e02d33c8713613
fatcat:3hfjrkeerfa3tgbtlmwd3o6qd4
Deep Multi-level Semantic Hashing for Cross-modal Retrieval
2019
IEEE Access
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INDEX TERMS Cross-modal retrieval, deep learning, hashing method, multi-label learning. ...
Due to its efficiency on storage and computing, hashing-based methods are broadly used for large scale cross-modal retrieval. ...
Cross-modal retrieval, also called cross-media retrieval, models the relationship among different modalities. ...
doi:10.1109/access.2019.2899536
fatcat:xynopqlgyfhe3ef6su55zqczim
Using Deep Cross Modal Hashing and Error Correcting Codes for Improving the Efficiency of Attribute Guided Facial Image Retrieval
[article]
2019
arXiv
pre-print
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In this paper, we propose a novel Error-Corrected Deep Cross Modal Hashing (CMH-ECC) method which uses a bitmap specifying the presence of certain facial attributes as an input query to retrieve relevant ...
In this architecture, we generate compact hash codes using an end-to-end deep learning module, which effectively captures the inherent relationships between the face and attribute modality. ...
Recently, application of deep learning to hash methods for uni-modal image retrieval [1, 2] and cross-modal retrieval [3, 4] have shown that end-to-end learning of feature extraction and hash coding ...
arXiv:1902.04139v1
fatcat:ychlkoe6yvaqfppi4xin5afysy
Deep Learning Techniques for Future Intelligent Cross-Media Retrieval
[article]
2020
arXiv
pre-print
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In this paper, we provide a novel taxonomy according to the challenges faced by multi-modal deep learning approaches in solving cross-media retrieval, namely: representation, alignment, and translation ...
Then, we present some well-known cross-media datasets used for retrieval, considering the importance of these datasets in the context in of deep learning based cross-media retrieval approaches. ...
Representations Data representations in cross-modal retrieval has always been a difficult task in deep learning. ...
arXiv:2008.01191v1
fatcat:t63bg55w2vdqjcprzaaidrmprq
Cross-Model Hashing Retrieval Based on Deep Residual Network
2021
Computer systems science and engineering
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In the process of mapping, the distance measurement of the original distance measurement and the common feature space are kept unchanged as far as possible to improve the accuracy of Cross-Modal Retrieval ...
In the era of big data rich in We Media, the single mode retrieval system has been unable to meet people's demand for information retrieval. ...
Acknowledgement: This paper would like to thank all the authors cited in the reference for their contributions to this field. ...
doi:10.32604/csse.2021.014563
fatcat:maw3votu7bdl5csccvqniby65i
Unsupervised Generative Adversarial Cross-modal Hashing
[article]
2017
arXiv
pre-print
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learning to exploit the underlying manifold structure of cross-modal data. ...
helpful to capture meaningful nearest neighbors of different modalities for cross-modal retrieval. ...
Therefore, cross-modal hashing has been proposed to meet this kind of retrieval demands in large scale cross-modal databases. ...
arXiv:1712.00358v1
fatcat:sxe6tprexzfy3h6iknjywwrf7u
Composite Correlation Quantization for Efficient Multimodal Retrieval
2016
Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval - SIGIR '16
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While hashing methods have shown great potential in achieving this goal, current attempts generally fail to learn isomorphic hash codes in a seamless scheme, that is, they embed multiple modalities in ...
a continuous isomorphic space and separately threshold embeddings into binary codes, which incurs substantial loss of retrieval accuracy. ...
The first two tasks are intra-modal retrieval and the last two tasks are cross-modal retrieval. ...
doi:10.1145/2911451.2911493
dblp:conf/sigir/LongCWY16
fatcat:y7omekozmjghzjztzn3wtij3cq
Query by Video: Cross-modal Music Retrieval
2019
Zenodo
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Cross-modal retrieval learns the relationship between the two types of data in a common space so that an input from one modality can retrieve data from a different modality. ...
To retrieve music for an input video, the trained model ranks tracks in the music database by cross-modal distances to the query video. ...
Cross-modal Audio-Visual Retrieval Cross-modal retrieval has received increasing attention in the recent years. ...
doi:10.5281/zenodo.3527881
fatcat:cwwcc6objbca7puhyt5rbxln6u
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