A review on generative adversarial networks: Algorithms, theory, and applications
Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …
however, they have been studied since 2014, and a large number of algorithms have been …
Unsupervised contrastive cross-modal hashing
In this paper, we study how to make unsupervised cross-modal hashing (CMH) benefit from
contrastive learning (CL) by overcoming two challenges. To be exact, i) to address the …
contrastive learning (CL) by overcoming two challenges. To be exact, i) to address the …
Deep multimodal representation learning: A survey
W Guo, J Wang, S Wang - Ieee Access, 2019 - ieeexplore.ieee.org
Multimodal representation learning, which aims to narrow the heterogeneity gap among
different modalities, plays an indispensable role in the utilization of ubiquitous multimodal …
different modalities, plays an indispensable role in the utilization of ubiquitous multimodal …
Deep joint-semantics reconstructing hashing for large-scale unsupervised cross-modal retrieval
Cross-modal hashing encodes the multimedia data into a common binary hash space in
which the correlations among the samples from different modalities can be effectively …
which the correlations among the samples from different modalities can be effectively …
Deep graph-neighbor coherence preserving network for unsupervised cross-modal hashing
Unsupervised cross-modal hashing (UCMH) has become a hot topic recently. Current
UCMH focuses on exploring data similarities. However, current UCMH methods calculate …
UCMH focuses on exploring data similarities. However, current UCMH methods calculate …
Cross-modal retrieval: a systematic review of methods and future directions
With the exponential surge in diverse multi-modal data, traditional uni-modal retrieval
methods struggle to meet the needs of users demanding access to data from various …
methods struggle to meet the needs of users demanding access to data from various …
Survey on deep multi-modal data analytics: Collaboration, rivalry, and fusion
Y Wang - ACM Transactions on Multimedia Computing …, 2021 - dl.acm.org
With the development of web technology, multi-modal or multi-view data has surged as a
major stream for big data, where each modal/view encodes individual property of data …
major stream for big data, where each modal/view encodes individual property of data …
Multi-modal hashing for efficient multimedia retrieval: A survey
L Zhu, C Zheng, W Guan, J Li, Y Yang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the explosive growth of multimedia contents, multimedia retrieval is facing
unprecedented challenges on both storage cost and retrieval speed. Hashing technique can …
unprecedented challenges on both storage cost and retrieval speed. Hashing technique can …
Modality-invariant asymmetric networks for cross-modal hashing
Cross-modal hashing has garnered considerable attention and gained great success in
many cross-media similarity search applications due to its prominent computational …
many cross-media similarity search applications due to its prominent computational …
Creating something from nothing: Unsupervised knowledge distillation for cross-modal hashing
In recent years, cross-modal hashing (CMH) has attracted increasing attentions, mainly
because its potential ability of mapping contents from different modalities, especially in …
because its potential ability of mapping contents from different modalities, especially in …