CrossModel Alignment CrossModel Alignment 目前的研究主要都是encode句子和视频片段为无结构的全局表示,用于多模态交互和融合。 本文提出的方法是SVMR(semantics-enriched video moment retrieval method)。能够清楚的获取分级多粒度的语义信息。 利用start and end time-aware filter kernels with visual cues去完成VMR...
In order to address these issues, we propose a Cross-modal Alignment with Graph Reasoning (CAGR) model, in which the refined cross-modal features in the common feature space are learned and then a fine-grained cross-modal alignment method is implemented. Specifically, we introduce a graph ...
Align as Ideal: Cross-Modal Alignment Binding forFederated Medical Vision-Language Pre-trainingZitao ShuaiEECS DepartmentUniversity of MichiganAnn Arbor, MI 48105ztshuai@umich.eduLiyue Shen ∗EECS DepartmentUniversity of MichiganAnn Arbor, MI 48105liyues@umich.eduAbstractVision-language pre-training (...
根据上述观察,作者通过 Generalized Zero-Shot Classification(GZSC)的Aligned Cross-Modal Representations(ACMR),提出了一种新的 VAE 网络。 整体概念图 创新点 提出了 ACMR,并在四个公开数据集上都取得了 SOTA 的性能 提出了一种新的 Vision-Semantic Alignment(VSA)方法,用于加强跨模态特征对齐 提出了一种新的 ...
Annotation Efficient Cross-Modal Retrieval with Adversarial Attentive Alignment (MM2019) Cross-Modal Retrieval 主要问题:image-text的注释平行语料库难以获得,或代价高昂。如何在使用尽可能少的注释对语料库的情况下来进行有效的跨模态检索任务。 主要挑战:人工注释文本与机器生成的注释 [论文笔记]多模态数据集预处理...
In this paper, we introduce Cross-modal Alignment with mixture experts Neural Network (CameNN) recommendation model for intral-city retail industry, which aims to provide fresh foods and groceries retailing within 5 hours delivery service arising for the outbreak of Coronavirus disease (COVID-19) ...
Mitigate the Gap: Investigating Approaches for Improving Cross-Modal Alignment in CLIP This is the official implementation of AlignCLIP and provides the source code for pre-training SharedCLIP as well as AlignCLIP. The implementation is based on the OpenCLIP. 🏃 We're currently running training...
Linguistic-Aware Patch Slimming Framework for Fine-grained Cross-Modal Alignment, CVPR, 2024 - CrossmodalGroup/LAPS
In this context, we introduce a cross-modal pre-trained language model, called Speech-Text BERT (ST-BERT), to tackle end-to-end spoken language understanding (E2E SLU) tasks. Taking phoneme posterior and subword-level text as an input, ST-BERT learns a contextualized cross-modal alignment ...
In prelimi-nary experiments, we extended this work to anothermodality: we found out that, in VQG, without anysupervision between the images and the questions,the cross-modal alignment was not successfullylearnt. This discrepancy between multi-lingual andmulti-modal results might f ind its root ...