Results 231 to 240 of about 64,981 (259)

HCMSL: Hybrid Cross-modal Similarity Learning for Cross-modal Retrieval

ACM Transactions on Multimedia Computing, Communications, and Applications, 2021
The purpose of cross-modal retrieval is to find the relationship between different modal samples and to retrieve other modal samples with similar semantics by using a certain modal sample. As the data of different modalities presents heterogeneous low-level feature and semantic-related high-level features, the main problem of cross-modal retrieval is ...
Chengyuan Zhang, Jiayu Song, Xiaofeng Zhu, Lei Zhu, Shichao Zhang   +4 more
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Deep Supervised Cross-Modal Retrieval

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Cross-modal retrieval aims to enable flexible retrieval across different modalities. The core of cross-modal retrieval is how to measure the content similarity between different types of data. In this paper, we present a novel cross-modal retrieval method, called Deep Supervised Cross-modal Retrieval (DSCMR).
Liangli Zhen, Peng Hu, Xu Wang, Dezhong Peng   +3 more
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Cross-Modality Personalization for Retrieval

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Existing captioning and gaze prediction approaches do not consider the multiple facets of personality that affect how a viewer extracts meaning from an image. While there are methods that consider personalized captioning, they do not consider personalized perception across modalities, i.e.
Nils Murrugarra-Llerena, Adriana Kovashka   +1 more
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Multi-label Cross-Modal Retrieval

2015 IEEE International Conference on Computer Vision (ICCV), 2015
In this work, we address the problem of cross-modal retrieval in presence of multi-label annotations. In particular, we introduce multi-label Canonical Correlation Analysis (ml-CCA), an extension of CCA, for learning shared subspaces taking into account high level semantic information in the form of multi-label annotations.
Viresh Ranjan, Nikhil Rasiwasia, C. V. Jawahar   +2 more
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Active Supervised Cross-Modal Retrieval

IEEE Transactions on Pattern Analysis and Machine Intelligence
Supervised Cross-Modal Retrieval (SCMR) achieves significant performance with the supervision provided by substantial label annotations of multi-modal data. However, the requirement for large annotated multi-modal datasets restricts the use of supervised cross-modal retrieval in many practical scenarios. Active Learning (AL) has been proposed to reduce
Huaiwen Zhang, Yang Yang, Fan Qi, Shengsheng Qian, Changsheng Xu   +4 more
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Geometric Matching for Cross-Modal Retrieval

IEEE Transactions on Neural Networks and Learning Systems
Despite its significant progress, cross-modal retrieval still suffers from one-to-many matching cases, where the multiplicity of semantic instances in another modality could be acquired by a given query. However, existing approaches usually map heterogeneous data into the learned space as deterministic point vectors.
Zheng Wang, Zhenwei Gao, Yang Yang, Guoqing Wang, Chengbo Jiao, Heng Tao Shen   +5 more
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Semantics Disentangling for Cross-Modal Retrieval

IEEE Transactions on Image Processing
Cross-modal retrieval (e.g., query a given image to obtain a semantically similar sentence, and vice versa) is an important but challenging task, as the heterogeneous gap and inconsistent distributions exist between different modalities. The dominant approaches struggle to bridge the heterogeneity by capturing the common representations among ...
Zheng Wang, Xing Xu, Jiwei Wei, Ning Xie, Yang Yang, Heng Tao Shen   +5 more
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Cross-Modal Retrieval With Noisy Labels

2020 IEEE International Conference on Image Processing (ICIP), 2020
Cross-modal retrieval is an important field of study for design of algorithms to effectively retrieve items from one modality when provided with a query from another modality. Recent progress in this field have shown that supervised algorithms perform significantly better than their unsupervised counterparts by utilizing the label information.
Devraj Mandal, Soma Biswas
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Cross-modal Retrieval with Label Completion

Proceedings of the 24th ACM international conference on Multimedia, 2016
Cross-modal retrieval has been attracting increasing attention because of the explosion of multi-modal data, e.g., texts and images. Most supervised cross-modal retrieval methods learn discriminant common subspaces minimizing the heterogeneity of different modalities by exploiting the label information.
Xing Xu, Fumin Shen, Yang Yang, Heng Tao Shen, Li He, Jingkuan Song   +5 more
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Principal affinity based cross-modal retrieval

2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR), 2015
Multimedia content is increasingly available in multiple modalities. Each modality provides a different representation of the same entity. This paper studies the problem of joint representation of the text and image components of multimedia documents. However, most existing algorithms focus more on inter-modal connection rather than intramodal feature ...
Jian Liang, Dong Cao, Ran He, Zhenan Sun, Tieniu Tan   +4 more
openaire   +1 more source