《Retrieving Multimodal Information for Augmented Generation: A Survey》是一篇由新加坡南洋理工大学、新加...
一些著名的基于图像的视觉知识提取系统如表2a所示,可用于通过图像标记构建MMKG。根据要链接的符号类别,将图像链接到符号的过程可分为几个细分任务:视觉实体/概念提取(第3.1.1节)、视觉关系提取(第3.1.2节)和视觉事件提取(第3.1.3节)。 (2)用KG标记图像。 符号基础是指找到适当的多模态数据项(如图像)以表示传统...
基于图神经网络的消息传递思想,我们设计了一个多模态图卷积网络(Multi-modal Graph Convolution Network,MMGCN)框架,该框架可以生成用户和微视频特定模态的表征,以更好地捕捉用户的偏好。具体地说,我们在每个模态上构造一个用户-项目二分图(bipartite graph),并用其邻接节点的拓扑结构和特征来丰富每个节点的表征。通过...
surveycensusagent based modeling (ABM)NetLogoexternal influencesModern survey data collection systems must balance cost and quality while supporting multiple response modes (paper, internet, telephone and personal interview) and addressing unpredictable respondent behavior. The next generation of survey ...
Metaphor is understanding one thing in terms of another. Metaphors can be experienced in two types in relation to their modes: monomodal and multimodal metaphors. Taking for granted that conceptual metaphor is a matter of thought and action entails that other modes than verbal/linguistic one can ...
论文精读：自动驾驶领域中的多模态3D目标检测：调查 摘要背景：自动驾驶技术在过去10年快速发展，实现全自动驾驶仍面临挑战。自动驾驶车辆通常配备多种传感器以减少感知难度，但融合传感器数据和利用其互补特性是当前趋势。然而，这一任务不容易处理，传感器数据可能互相影响或互为噪声。贡献：本研究深入研究了...
A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets. Vis Comput , 2022 , 38: 2939 -2970 CrossRef PubMed Google Scholar [44] Liu Q, Wang W, and Jackson P. A visual voice activity detection method with adaboosting. Sensor Signal Processi...
A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets. Vis Comput , 2022 , 38: 2939 -2970 CrossRef PubMed Google Scholar [44] Liu Q, Wang W, and Jackson P. A visual voice activity detection method with adaboosting. Sensor Signal Processi...
Multi-modal Sensor Fusion for Auto Driving Perception: A Survey 这篇文章结构清晰,介绍什么环境感知存在哪些任务,存在哪些数据集,介绍点云和图像的表示方法,其实就是分类,提出了一种新的分类表示方法,最后说了挑战 摘要 多模态融合是自动驾驶系统感知的一项基本任务,近年来引起了许多研究者的兴趣。然而,由于原始数...
survey questions in a proxy means test (PMT) to estimate whether a household is below the poverty line. We show that the inclusion of visual features reduces the mean error in poverty rate estimates from 4.09% to 3.88% over a nationally representative out-of-sample test set. In addition to...