VSE++: Improving Visual-Semantic Embeddings with Hard Negatives

时间 2021-02-19

标签 html web 网络 svg spa xml htm blog 图片栏目 HTML 繁體版

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1、前言 1.论文要解决的问题：输入： MSCOCO，Flickr30K 输出： image to text （text to image）:rankhtml 2, 本文的方法创新：提出了一种新的计算loss的方案，主要针对与hard negtive,加大样本与hard negtive 的距离web 2、论文方法 Embedding 1) 图像采用VGG19或者ResNet152进行特征提取

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1. Improving Chemical Named Entity Recognition in Patents with Contextualized Word Embeddings
2. Improved Embeddings with Easy Positive Triplet Mining
3. Look, Imagine and Match: Improving Textual-Visual Cross-Modal Retrieval with Generative Models
4. Question Answering with Subgraph Embeddings笔记
5. True(False) Positives (Negatives)
6. Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
7. 论文解读：Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
8. Bootstrapping Face Detection with Hard Negative Examples
9. Tune Your Hard Disk with hdparm
10. ACL2020《Improving Entity Linking through Semantic Reinforced Entity Embeddings》阅读笔记

>>更多相关文章<<