Deep Supervised Cross-modal Retrieval 摘要 在本文中提出了一种新颖的跨模式检索方法,称为深度监督跨模式检索(Deep Supervised Cross-modal Retrieval, DSCMR)。它旨在找到一个通用的表示空间,在其中可以直接比较来自不同模态的样本。 共享 提出了一个监督的跨模态学习结构作为不同模态的桥梁。它可以通过保留语义的区分...
To combat this challenge, the paper proposes a deep cross-modal hashing framework for geo-multimedia retrieval, termed as Triplet-based Deep Cross-Modal Retrieval (TDCMR), which utilizes deep neural network and an enhanced triplet constraint to capture high-level semantics. Besides, ...
过去一段时间在研究cross-modal hashing领域,这个领域可以看作是cross-modal retrieval领域的扩展,也可以看作是image retrieval hashing领域的扩展。该领域在15年通过发表于CVPR上的论文SePH("Semantics-preserving hashing for cross-view retrieval")逐渐受到大家关注,也是从这时开始,国人开始大量引入这个领域。 到2020年...
蓝色块强调了视觉流的三个部分,绿色块表示损失函数。 3.1 Cross-Modal Relation Guided Network 3.1.1 Visual Stream of CRGN: 在图1中,视频流利用图像局部分支、图像全局分支和关系嵌入模块生成最终的图像嵌入。图像全局分支生成全局引导特征(全局上下文),图像局部分支提取图像区域特征(语义概念)。关系嵌入模块利用全局...
Deep Cross-modal Retrieval Stacked Cross Attention for Image-Text Matching, ECCV 2018. [paper] [code] Multi-Level Visual-Semantic Alignments with Relation-Wise Dual Attention Network for Image and Text Matching, IJCAI 2019. [paper] Position Focused Attention Network for Image-Text Matching, IJCAI ...
Adaptive Document Retrieval for Deep Question Answering EMNLP 2018 Adaptive Document Retrieval for Deep Question Answering 背景 阅读理解模型的处理过程可以分为两步: 从文档集中根据问题检索可能包含答案的文档 从检索到的文档中寻找包含答案的具体区域 现有的方法在以上的两步各自都可以取得不错的效果,但是很少有...
Deep Semantic-Preserving Reconstruction Hashing for Unsupervised Cross-Modal Retrieval. Deep hashing is the mainstream algorithm for large-scale cross-modal retrieval due to its high retrieval speed and low storage capacity, but the problem of reconstruction of modal semantic information is still very ch...
Cross-modal retrievalAdversarial learningMetric learningCross-modal retrieval has become a highlighted research topic, to provide flexible retrieval experience across multimedia data such as image, video, text and audio. The core of existing cross-modal......
DRSL: Deep Relational Similarity Learning for Cross-modal Retrieval-多模态学习总结,程序员大本营,技术文章内容聚合第一站。
As the rapid development of deep neural networks, multi-modal learning techniques are widely concerned. Cross-modal retrieval is an important branch of multimodal learning. Its fundamental purpose is to reveal the relation between different modal samples