论文链接:Negative-Aware Attention Framework for Image-Text Matching(基于负感知注意力的图文匹配,CVPR2022) 代码主页:https://github.com/CrossmodalGroup/NAAF 主要优势 (Highlights): 1)不额外添加任何学习参数前提下,在基础基线SCAN上取得显著性能提升,达到SOTA; 2)模型设计简单有效,只需要SCAN 的文本-图像(Text...
做"image-text matching" 这个 topic 有大半年的时间了,从 CVPR2020 鸽到IJCAI2020,code 写了不少,实验也做了不少,但是最后还是没能做出来,接下来要去 MSRA 实习一段时间,不知道又要鸽到什么时候了。 在实验后期卡住的时候,我看到了一些新颖的 VQA 的工作,感觉蛮有意思。本篇文章主要结合这些 VQA 模型和我...
Text-image matching has been one of the most popular ones among them. Most methods involve two phases: 1) training: two neural networks (one image encoder and one text encoder) are learned end-to-end, mapping texts and images into a joint space, where vectors (either texts or images) wi...
代码使用的很巧妙: classContrastiveLoss(nn.Module):def__init__(self,margin=0,max_violation=False):super(ContrastiveLoss,self).__init__()self.margin=marginself.max_violation=max_violationdefforward(self,scores):# compute image-sentence score matrixdiagonal=scores.diag().view(scores.size(0),1)d...
Image-text retrievalMulti-subspace learningCross-modal matchingJoint representation learning has been an attractive way to solve image-text retrieval problem due to its efficiency on both time and storage. On the one hand, the most classical methods model the joint semantic subspace with respect to ...
This is Negative-Aware Attention Framework for Image-Text Matching, source code of NAAF. The paper is accepted by CVPR2022. Download Paper. Its Chinese blog can be found here. It is built on top of the SCAN in PyTorch. Our series of work based on optimal discriminative learning is publishe...
MatchPyramid来自Liang Pang等在2016发表的一篇文章Text Matching as Image Recognition,大意为利用图像识别的方式进行文本匹配。 二、思路 对于文本匹配,基本思路如下述公式: 其中T为文本,函数θθθ代表将文本转换为对应的表示,函数FFF则代表两个文本表示之间的交互关系。 由侧重点不同可分为表示方法与交互方法,即注重...
image and text. In this paper, we propose a Consensus-Aware Visual-Semantic Embedding (CVSE) model to incorporate the consensus information, namely the commonsense knowledge shared between both modalities, into image-text matching. Specifically, the consensus information is exploited by computing ...
Benchmarks and Challenges Doaa B. Ebaid1 · Magda M. Madbouly1 · Adel A. El‑Zoghabi1 Received: 2 January 2023 / Accepted: 26 April 2023 © The Author(s) 2023 Abstract Nowadays, image–text matching (retrieval) has frequently attracted attention due to the...
Text_Matching(文本匹配算法) 文本匹配是自然语言理解中的一个核心问题,它可以应用于大量的自然语言处理任务中,例如信息检索、问答系统、复述问题、对话系统、机器翻译等等。这些自然语言处理任务在很大程度上都可以抽象成文本匹配问题,比如信息检索可以归结为搜索词和文档资源的匹配,问答系统可以归结为问题和候选答案的匹配...