Comparative analysis on cross-modal information retrieval: A review
Human beings experience life through a spectrum of modes such as vision, taste, hearing,
smell, and touch. These multiple modes are integrated for information processing in our …
smell, and touch. These multiple modes are integrated for information processing in our …
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 …
Deep supervised cross-modal retrieval
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 …
of cross-modal retrieval is how to measure the content similarity between different types of …
[PDF][PDF] Cross-modality person re-identification with generative adversarial training.
Person re-identification (Re-ID) is an important task in video surveillance which
automatically searches and identifies people across different cameras. Despite the …
automatically searches and identifies people across different cameras. Despite the …
HSME: Hypersphere manifold embedding for visible thermal person re-identification
Person Re-identification (re-ID) has great potential to contribute to video surveillance that
automatically searches and identifies people across different cameras. Heterogeneous …
automatically searches and identifies people across different cameras. Heterogeneous …
Triplet-based deep hashing network for cross-modal retrieval
Given the benefits of its low storage requirements and high retrieval efficiency, hashing has
recently received increasing attention. In particular, cross-modal hashing has been widely …
recently received increasing attention. In particular, cross-modal hashing has been widely …
CM-GANs: Cross-modal generative adversarial networks for common representation learning
It is known that the inconsistent distributions and representations of different modalities, such
as image and text, cause the heterogeneity gap, which makes it very challenging to correlate …
as image and text, cause the heterogeneity gap, which makes it very challenging to correlate …
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 …
Unsupervised generative adversarial cross-modal hashing
Cross-modal hashing aims to map heterogeneous multimedia data into a common
Hamming space, which can realize fast and flexible retrieval across different modalities …
Hamming space, which can realize fast and flexible retrieval across different modalities …
Learning dual semantic relations with graph attention for image-text matching
Image-Text Matching is one major task in cross-modal information processing. The main
challenge is to learn the unified visual and textual representations. Previous methods that …
challenge is to learn the unified visual and textual representations. Previous methods that …