早期融合使用特征融合技术来学习联合视觉文本语义表示,然后进行情感分析。后期融合通过利用不同的特定领域技术分别处理图像和文本信息,然后利用所有模态的情感标签来获得最终结果。最近,You等人提出了一种用于图文情感分析的跨模态一致回归(CCR)方案,并实现了优于先前融合模型的最佳性能。然而,由于视觉和文本信息之间的语义鸿...
Cross-modality attentionDeep neural networksMultispectral pedestrian detection is an emerging solution with great promise in many around-the-clock applications, such as automotive driving and security surveillance. To exploit the complementary nature and remedy contradictory appearance between modalities, in ...
In this paper, we propose the Cross-Modality Attention Contrastive Language-Image Pre-training (CMA-CLIP), a new framework which unifies two types of cross-modality attentions, sequence-wise attention and modality-wise attention, to effectively fuse information from image and text pairs. The ...
machine-learning deep-learning time-series language-model time-series-analysis time-series-forecast time-series-forecasting multimodal-deep-learning cross-modality multimodal-time-series cross-modal-learning prompt-tuning large-language-models Updated Nov 3, 2024 Python whwu95 / Cap4Video Star 248...
原论文:SYNTHESIZER: Rethinking Self-Attention in Transformer Models 1 前言 什么是自注意力? 2017 年,Vaswani 等人 [1] 提出了 Transformer 模型,在众多领域取得了成功的应用,证明了它相比于自回归模型和循环模型的优势。 Transfor…阅读全文 赞同60 19 条评论 分享收藏 ...
MIT license Cross-Modality Interactive Attention Network for Multispectral Pedestrian Detection Created by Lu Zhang, Institute of Automation, Chinese Academy of Science. Introduction We propose a novel single-shot multispectral pedestrian detector, called CIAN, that utilizes the cross-modality (e.g., col...
doi:10.1016/S1053-8119(96)80201-1Spoont, Michele R.Pardo, José V.NeuroimageSpoont M, Pardo JV (1996): Cross-modality selective attention: Modulation of rCBF by stimulus information flow. Neuroimage 3:S199.
5.Multi-Modality Cross Attention Network for Image and Sentence Matching 方法:作者提出了一种新颖的图像和句子匹配方法,通过在统一的深度模型中联合建模跨模态和内部模态关系。作者首先提取显著的图像区域和句子标记。然后,应用所提出的自注意模块和交叉注意力模块来利用片段之间的复杂细粒度关系。最后,通过最小化基于...
Cross-modal retrieval, as a more effective and in-demand search method, has garnered significant research attention in today’s society. Commonly used cross-modal retrieval methods1,2,3,4 employ real-valued vectors to represent multimodal data. However, these methods require extensive computation ...
Review-Aware Neural Recommendation with Cross-Modality Mutual Attention 来源:CIKM 21 摘要:双塔神经网络广泛应用于评论感知的推荐系统中(如图一的DeepCoNN模型),其两个编码器分别从评论中学习用户和项目的表示。然而,作者认为这种这种体系结构隔离了两个编码器之间的信息交换,导致推荐精度不佳。为此,作者提出了一种新...