Learning Semantic Concepts and Order for Image and Sentence Matching笔记

时间 2020-12-26

标签论文笔记机器学习人工智能繁體版

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SCO模型阅读笔记论文：Learning Semantic Concepts and Order for Image and Sentence Matching 发表会议：CVPR2018 作者：一、为什么看？好多关于图像-文本检索的文章，但是大多数都忽略了图像的语义顺序，当语义顺序被忽略时，会造成检索不准确，图像和文本的语义完全相反。看点：图像的语义顺序如何构建应用：于跨模态图像-文本

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1. 《Learning Semantic Concepts and Order for Image and Sentence Matching》
2. Learning Semantic Concepts and Order for Image and Sentence Matching笔记
3. 读论文，多区块处理：Learning Semantic Concepts and Order forImage and Sentence Matching
4. Semantic Sentence Matching with Densely-connected Recurrent and Co-attentive Information阅读笔记
5. Image-Text Matching and VQA
6. [AAAI2019] DRr-Net:Dynamic Re-read Netwok for Sentence Semantic Matching
7. MatchNet: Unifying Feature and Metric Learning for Patch-Based Matching
8. Locally Adaptive Color Correction for Underwater Image Dehazing and Matching
9. 语义分割--Learning Object Interactions and Descriptions for Semantic Image Segmentation
10. [论文笔记]FashionBERT: Text and Image Matching with Adaptive Loss for Cross-modal Retrieval
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1. 《Learning Semantic Concepts and Order for Image and Sentence Matching》
2. Learning Semantic Concepts and Order for Image and Sentence Matching笔记
3. 读论文，多区块处理：Learning Semantic Concepts and Order forImage and Sentence Matching
4. Semantic Sentence Matching with Densely-connected Recurrent and Co-attentive Information阅读笔记
5. Image-Text Matching and VQA
6. [AAAI2019] DRr-Net:Dynamic Re-read Netwok for Sentence Semantic Matching
7. MatchNet: Unifying Feature and Metric Learning for Patch-Based Matching
8. Locally Adaptive Color Correction for Underwater Image Dehazing and Matching
9. 语义分割--Learning Object Interactions and Descriptions for Semantic Image Segmentation
10. [论文笔记]FashionBERT: Text and Image Matching with Adaptive Loss for Cross-modal Retrieval

>>更多相关文章<<