标题：A Survey of Multimodal Composite Editing and Retrieval 作者：Suyan Li, Fuxiang Huang, Lei Zhang 单位：重庆大学 标签：多模态学习、图像检索、文本处理、人工智能 概述：这篇文章系统地回顾了多模态复合编辑和检索领域的研究进展，探讨了图像-文本复合编辑、图像-文本复合检索以及其他多模态复合检索的方法、应用场景和未来方向。
去年在跨模态检索/匹配 (cross-modal retrieval/matching) 方向开展了一些研究与应用,感觉比较有意思,所以想写点东西记录一下。这个研究方向并不是一个很"干净"的概念,它可以与 representation learning、contrastive learning、unsupervised leraning 等等概念交叉联系。并没有时间和能力写综述,思来想去就以研究较多的图文...
Cross-modal retrieval has drawn wide interest for retrieval across different modalities (such as text, image, video, audio, and 3-D model). However, existing methods based on a deep neural network often face the challenge of insufficient cross-modal training data, which limits the training ...
Introduction bidirectional retrieval 挑战 设计一种对元数据没有要求的跨模式模型 难以获得匹配的视频音乐对,视频和音乐之间的匹配标准比其他跨模态任务(例如,图像到文本的...用户评估 为了解决这个问题,我们将Recall@K(一种用于交叉模式检索的标准协议,尤其是在图像-文本检索[30],[33]中)应用到双向CBVMR任务 对于...
The rapid development of Deep Neural Networks (DNNs) in single-modal retrieval has promoted the wide application of DNNs in cross-modal retrieval tasks. Therefore, we propose a DNN-based method to learn the shared representation for each modality. Our method, hybrid representation learning (HRL),...
论文名称:GME: Improving Universal Multimodal Retrieval by Multimodal LLMs 论文链接:arxiv.org/abs/2412.1685 Huggingface:hf.co/Alibaba-NLP/gme-Q 摘要 通用多模态检索(UMR)旨在通过一个统一的模型实现跨各种模态的搜索,其中查询和候选项可以是纯文本、图像或两者的组合。之前的工作尝试采用多模态大语言模型(...
discriminative information reflected by labels and, hence, the retrieval accuracies of these methods are affected. To address these challenges, this paper introduces a simple yet effective supervised multimodal hashing method, called label consistent matrix factorization hashing (LCMFH), which focuses on...
学术范收录的Conference Cross-modal retrieval based on deep correlated network,目前已有全文资源,进入学术范阅读全文,查看参考文献与引证文献,参与文献内容讨论。学术范是一个在线学术交流社区,收录论文、作者、研究机构等信息,是一个与小木虫、知乎类似的学术讨
机器翻译 参考文献(52) 发布时间·被引用数·默认排序 Cross-Modal Center Loss for 3D Cross-Modal Retrieval Longlong JingElahe VahdaniJames S. TanYingli Tian Computer Vision and Pattern Recognition Jun 2021 Cross-modal retrieval aims to learn discriminative and modal-invariant features for data from di...