Zobrazeno 1 - 10
of 7 030
pro vyhledávání: '"Cross-modal Retrieval"'
Cross-modal hashing (CMH) has appeared as a popular technique for cross-modal retrieval due to its low storage cost and high computational efficiency in large-scale data. Most existing methods implicitly assume that multi-modal data is correctly labe
Externí odkaz:
http://arxiv.org/abs/2501.01699
Recent advancements in deep learning have significantly enhanced content-based retrieval methods, notably through models like CLIP that map images and texts into a shared embedding space. However, these methods often struggle with domain-specific ent
Externí odkaz:
http://arxiv.org/abs/2412.21009
Existing cross-modal retrieval methods typically rely on large-scale vision-language pair data. This makes it challenging to efficiently develop a cross-modal retrieval model for under-resourced languages of interest. Therefore, Cross-lingual Cross-m
Externí odkaz:
http://arxiv.org/abs/2412.13510
Given a query from one modality, few-shot cross-modal retrieval (CMR) retrieves semantically similar instances in another modality with the target domain including classes that are disjoint from the source domain. Compared with classical few-shot CMR
Externí odkaz:
http://arxiv.org/abs/2411.17454
The success of most existing cross-modal retrieval methods heavily relies on the assumption that the given queries follow the same distribution of the source domain. However, such an assumption is easily violated in real-world scenarios due to the co
Externí odkaz:
http://arxiv.org/abs/2410.15624
Deep hashing, due to its low cost and efficient retrieval advantages, is widely valued in cross-modal retrieval. However, existing cross-modal hashing methods either explore the relationships between data points, which inevitably leads to intra-class
Externí odkaz:
http://arxiv.org/abs/2410.15387
In the realm of cross-modal retrieval, seamlessly integrating diverse modalities within multimedia remains a formidable challenge, especially given the complexities introduced by noisy correspondence learning (NCL). Such noise often stems from mismat
Externí odkaz:
http://arxiv.org/abs/2408.01349
Cross-lingual cross-modal retrieval (CCR) aims to retrieve visually relevant content based on non-English queries, without relying on human-labeled cross-modal data pairs during training. One popular approach involves utilizing machine translation (M
Externí odkaz:
http://arxiv.org/abs/2409.19961
Implementing cross-modal hashing between 2D images and 3D point-cloud data is a growing concern in real-world retrieval systems. Simply applying existing cross-modal approaches to this new task fails to adequately capture latent multi-modal semantics
Externí odkaz:
http://arxiv.org/abs/2408.05711
Autor:
Zou, Qiang1 (AUTHOR) zouq@stu.xju.edu.cn, Cheng, Shuli1 (AUTHOR) cslxju@xju.edu.cn, Du, Anyu1 (AUTHOR), Chen, Jiayi1 (AUTHOR)
Publikováno v:
Entropy. Nov2024, Vol. 26 Issue 11, p911. 22p.
