通过整合词义消歧改进图像-文本匹配

IF 3.2 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Signal Processing Letters Pub Date : 2024-09-24 DOI:10.1109/LSP.2024.3466992
Xiao Pu;Ping Yang;Lin Yuan;Xinbo Gao
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引用次数: 0

摘要

这封信提出了一种新方法,通过在文本编码器中加入词义消歧(WSD)来增强图像与文本的匹配。我们的方法明确地对可能存在歧义的单词进行词义建模,从而完善图像和文本之间的语义理解。通过将轻量级 WSD 组件集成到匹配框架中,我们引入了一种感知机制来实现图像与文本的对齐,同时优化这两项任务。我们的 WSD 模块利用图注意网络(GAT)的强大功能,在广泛的单词上下文中运行,并通过多任务学习,从规模更大的预训练 WSD 模型中提炼知识。我们的实验证明了用从 WSD 方法中获得的意义表征来增强原始词嵌入的有效性。我们在两个广泛使用的图像-文本匹配基准上系统地评估了我们的方法与几种基准和最先进的方法的对比情况:MS-COCO 和 Flickr30K。结果表明,我们的方法显著提高了匹配准确率,凸显了我们提出的方法的功效。
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Improving Image-Text Matching by Integrating Word Sense Disambiguation
This letter presents a novel approach to enhance image-text matching by incorporating word sense disambiguation (WSD) within the text encoder. Our method explicitly models the senses of potentially ambiguous words, refining the semantic understanding between images and text. We introduce a sense-aware mechanism for image-text alignment by integrating a lightweight WSD component into the matching framework, optimizing both tasks simultaneously. Our WSD module operates on extensive word contexts, leveraging the power of graph attention networks (GAT), and distills knowledge from a substantially larger pre-trained WSD model through multi-task learning. Our experiments demonstrate the effectiveness of augmenting original word embeddings with sense representations derived from our WSD approach. We systematically evaluate our method against several baselines and state-of-the-art approaches on two widely-used image-text matching benchmarks: MS-COCO and Flickr30K. The results illustrate significant improvements in matching accuracy, highlighting the efficacy of our proposed approach.
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来源期刊
IEEE Signal Processing Letters
IEEE Signal Processing Letters 工程技术-工程:电子与电气
CiteScore
7.40
自引率
12.80%
发文量
339
审稿时长
2.8 months
期刊介绍: The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing. Papers published in the Letters can be presented within one year of their appearance in signal processing conferences such as ICASSP, GlobalSIP and ICIP, and also in several workshop organized by the Signal Processing Society.
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