(CVPR'22) COTS: Collaborative Two-Stream Vision-Language Pre-Training Model for Cross-Modal Retrieval (ECCV'22) TS2-Net: Token Shift and Selection Transformer for Text-Video Retrieval (ArXiv'22) M2HF: Multi-level Multi-modal Hybrid Fusion for Text-Video Retrieval (ArXiv'22)UATVR: Uncertaint...
·前言 上半年在写跨模态专题时,因为相关工作在投 paper,所以一些内容当时没有写出来。比较幸运 paper 上个月被接收了,所以把这部分工作简化成第5篇也分享下。对前 4 篇感兴趣的同学可以看文末链接。 本文脉络 combine GAN and infoNCE 不同的组合模式 场景应用讨论 01 — combine GAN and infoNCE 在专题的前...
cross-modal retrieval 指标《探究跨模态检索指标》 跨模态检索(cross-modal retrieval)是指在不同的数据模态之间进行相关内容的搜索和检索。在信息检索领域,跨模态检索已经成为一个热门的话题,因为我们现在可以访问到各种类型的数据,比如文本、图像、视频和音频等。针对这个主题,我们将首先从跨模态检索的定义开始,逐步...
本文探讨跨模态检索（Cross-Modal Retrieval）领域，特别是Adversarial Cross-Modal Retrieval（ACMR）这一具有创新性的方法。ACMR在2017年ACM Multimedia会议上获得最佳论文奖，为跨模态数据的检索提供了新的思路。该方法利用对抗学习（Adversarial Learning）和三元约束（Triplet Constraint）将图像和文本映射到公共...
Hashing has been extensively utilized in cross-modal retrieval due to its high efficiency in handling large-scale, high-dimensional data. However, most existing cross-modal hashing methods operate as offline learning models, which learn hash codes in a batch-based manner and prove to be inefficient...
The cross-modal retrieval problem is: given the representation of an entity in one modality, find its best representation in all other modalities. We propose a novel approach to this problem based on pairwise classification. The approach seamlessly applies to both the settings where ground-truth ...
Cross-modal hashing encodes heterogeneous multimedia data into compact binary code to achieve fast and flexible retrieval across different modalities. Due to its low storage cost and high retrieval efficiency, it has received widespread attention. Supervised deep hashing significantly improves search performa...
With the development of deep learning, more and more cross-modal hashing methods based on deep learning are proposed. However, most of these methods use a small batch to train a model. The large batch training can get better gradients and can improve training efficiency. In this paper, we ...
Cross-Domain Image Captioning via Cross-Modal Retrieval and Model Adaptation 来自 国家科技图书文献中心 喜欢 0 阅读量: 199 作者:W Zhao,X Wu,J Luo 摘要: In recent years, large scale datasets of paired images and sentences have enabled the remarkable success in automatically generating descriptions ...
但有时它并不是什么都知道。现在，我们有一种特殊的技巧，叫做 "检索-增强生成"（Retrieval-Augmented ...