Cross-modal retrieval: a systematic review of methods and future directions
With the exponential surge in diverse multimodal data, traditional unimodal retrieval
methods struggle to meet the needs of users seeking access to data across various …
methods struggle to meet the needs of users seeking access to data across various …
The State of the Art for Cross-Modal Retrieval: A Survey
Cross-modal retrieval, which aims to search for semantically relevant data across different
modalities, has received increasing attention in recent years. Deep learning, with its ability to …
modalities, has received increasing attention in recent years. Deep learning, with its ability to …
OMGH: Online manifold-guided hashing for flexible cross-modal retrieval
Cross-modal hashing hasrecently gained an increasing attention for its efficiency and fast
retrieval speed in indexing the multimedia data across different modalities. Nevertheless, the …
retrieval speed in indexing the multimedia data across different modalities. Nevertheless, the …
Partial multi-modal hashing via neighbor-aware completion learning
Multi-modal hashing technology can support large-scale multimedia retrieval well, because
of its fast query speed and low storage consumption. Although many multi-modal hashing …
of its fast query speed and low storage consumption. Although many multi-modal hashing …
Cross-modal semantic aligning and neighbor-aware completing for robust text–image person retrieval
T Gong, J Wang, L Zhang - Information Fusion, 2024 - Elsevier
Most existing text–image person re-identification (TIReID) methods are performed in an
ideal environment where both image and text instances are fully intact and identity …
ideal environment where both image and text instances are fully intact and identity …
A comprehensive empirical study of vision-language pre-trained model for supervised cross-modal retrieval
Cross-Modal Retrieval (CMR) is an important research topic across multimodal computing
and information retrieval, which takes one type of data as the query to retrieve relevant data …
and information retrieval, which takes one type of data as the query to retrieve relevant data …
Fine-grained Prototypical Voting with Heterogeneous Mixup for Semi-supervised 2D-3D Cross-modal Retrieval
This paper studies the problem of semi-supervised 2D-3D retrieval which aims to align both
labeled and unlabeled 2D and 3D data into the same embedding space. The problem is …
labeled and unlabeled 2D and 3D data into the same embedding space. The problem is …
Ugncl: Uncertainty-guided noisy correspondence learning for efficient cross-modal matching
Cross-modal matching has recently gained significant popularity to facilitate retrieval across
multi-modal data, and existing works are highly relied on an implicit assumption that the …
multi-modal data, and existing works are highly relied on an implicit assumption that the …
C3CMR: Cross-Modality Cross-Instance Contrastive Learning for Cross-Media Retrieval
Cross-modal retrieval is an essential area of representation learning, which aims to retrieve
instances with the same semantics from different modalities. In real implementation, a key …
instances with the same semantics from different modalities. In real implementation, a key …
Parallel learned generative adversarial network with multi-path subspaces for cross-modal retrieval
Z Li, H Lu, H Fu, G Gu - Information Sciences, 2023 - Elsevier
Cross-modal retrieval aims to narrow the heterogeneity gap between different modalities,
such as retrieving images through texts or vice versa. One of the key challenges of cross …
such as retrieving images through texts or vice versa. One of the key challenges of cross …