因为cross-modal hashing的低存储和高效的查询能力,被广泛用于多媒体的相似度检索中。本论文提出了一个deep cross-modal hashing(DCMH),首次将feature learning和hash-code learning结合到同一个框架中。 DCMH的框架: 该框架包含两个deep Neural Network,一个是提取image的feature,另一个提取text中的feature。 CNN的...
也是从17年左右开始,就有基于深度学习的cross-modal hashing。 DCMH("Deep cross-modal hashing") 该论文可以是基于deep learning 的cross-modal hashing的开始,为deep cross-modal hashing提供了一套完整的计算架构。 deep learning引入后的问题 本文将hash当作我们要学习的特征,通过神经网络对不同实例提取特征,然后...
在2016年年初,李武军老师带领的研究团队在arXiv上发布了一篇文章,其中介绍了一种跨模态深度哈希算法DCMH(Deep Cross-Modal Hashing)[11]。这篇文章中,作者利用一个两路的深度模型将两种不同模态的数据(文章中是文本和图像)变换到一个公共空间,并要求相似的样本在这个公共空间中相互靠近,如下图所示。通过同时对图像...
In this paper,\nwe propose a novel cross-modal hashing method, called deep crossmodal hashing\n(DCMH), by integrating feature learning and hash-code learning into the same\nframework. DCMH is an end-to-end learning framework with deep neural networks,\none for each modality, to perform ...
In this paper, we propose a novel CMH method, called deep cross-modal hashing (DCMH), by integrating feature learning and hash-code learning intothe same framework. DCMH is an end-to-end learning framework with deep neural networks, one for each modality, to perform feature learning from ...
在2016年年初,李武军老师带领的研究团队在arXiv上发布了一篇文章,其中介绍了一种跨模态深度哈希算法DCMH(Deep Cross-Modal Hashing)[11]。这篇文章中,作者利用一个两路的深度模型将两种不同模态的数据(文章中是文本和图像)变换到一个公共空间,并要求相似的样本在这个公共空间中相互靠近,如下图所示。通过同时对图像...
DCMH_tensorflow/DCMH_tensorflow .DS_Store README.md README Introduction This package contains the source code for the following paper: Qing-Yuan Jiang and Wu-Jun Li.Deep Cross-Modal Hashing.CVPR-2017. Author:Qing-Yuan JiangandWu-Jun Li ...
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 and successfully used in multimedia similarity search applications. However, almost all existing methods employing cross-...
Qu, L. et al. Cross-modal coherent registration of whole mouse brains.Nat. Methods19, 111–118 (2022). ArticleCASPubMedGoogle Scholar Hatamizadeh, A. et al. UNETR: Transformers for 3D Medical Image Segmentation. InIEEE/CVF Winter Conference on Applications of Computer Vision (WACV)1748–1758...
在2016年年初,李武军老师带领的研究团队在arXiv上发布了一篇文章,其中介绍了一种跨模态深度哈希算法DCMH(Deep Cross-Modal Hashing)[11]。这篇文章中,作者利用一个两路的深度模型将两种不同模态的数据(文章中是文本和图像)变换到一个公共空间,并要求相似的样本在这个公共空间中相互靠近,如下图所示。通过同时对图像...