Iterative graph attention memory network for cross-modal retrieval
How to eliminate the semantic gap between multi-modal data and effectively fuse multi-
modal data is the key problem of cross-modal retrieval. The abstractness of semantics …
modal data is the key problem of cross-modal retrieval. The abstractness of semantics …
Adversarial graph convolutional network for cross-modal retrieval
The completeness of semantic expression plays an important role in cross-modal retrieval
tasks, which contributes to align the cross-modal data and thus narrow the modality gap. But …
tasks, which contributes to align the cross-modal data and thus narrow the modality gap. But …
Adaptive label-aware graph convolutional networks for cross-modal retrieval
The cross-modal retrieval task has raised continuous attention in recent years with the
increasing scale of multi-modal data, which has broad application prospects including …
increasing scale of multi-modal data, which has broad application prospects including …
Bridging multimedia heterogeneity gap via graph representation learning for cross-modal retrieval
Abstract Information retrieval among different modalities becomes a significant issue with
many promising applications. However, inconsistent feature representation of various …
many promising applications. However, inconsistent feature representation of various …
Two-stage deep learning for supervised cross-modal retrieval
J Shao, Z Zhao, F Su - Multimedia Tools and Applications, 2019 - Springer
This paper deals with the problem of modeling internet images and associated texts for
cross-modal retrieval such as text-to-image retrieval and image-to-text retrieval. Recently …
cross-modal retrieval such as text-to-image retrieval and image-to-text retrieval. Recently …
Scalable deep multimodal learning for cross-modal retrieval
Cross-modal retrieval takes one type of data as the query to retrieve relevant data of another
type. Most of existing cross-modal retrieval approaches were proposed to learn a common …
type. Most of existing cross-modal retrieval approaches were proposed to learn a common …
Category alignment adversarial learning for cross-modal retrieval
S He, W Wang, Z Wang, X Xu, Y Yang… - … on Knowledge and …, 2022 - ieeexplore.ieee.org
Cross-modal retrieval aims to retrieve one semantically similar media from multiple media
types based on queries entered by another type of media. An intuitive idea is to map …
types based on queries entered by another type of media. An intuitive idea is to map …
Heterogeneous memory enhanced graph reasoning network for cross-modal retrieval
Cross-modal retrieval (CMR) aims to retrieve the instances of a specific modality that are
relevant to a given query from another modality, which has drawn much attention because of …
relevant to a given query from another modality, which has drawn much attention because of …
Hcmsl: Hybrid cross-modal similarity learning for cross-modal retrieval
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 …
samples and to retrieve other modal samples with similar semantics by using a certain …
Similarity and diversity induced paired projection for cross-modal retrieval
The heterogeneous gap among cross modalities is a critical problem in many applications
(eg, retrieval). Considering that the main purpose of cross-modal learning is to learn a …
(eg, retrieval). Considering that the main purpose of cross-modal learning is to learn a …