【Up-Sampling】《CARAFE：Content-Aware ReAssembly of FEatures》

時間 2021-01-21

標籤 CNN 简体版

原文原文鏈接

ICCV-2019 oral presentation 文章目錄 1 Background and Motivation 2 Advantages / Contributions 3 Method 3.1 Kernel Prediction Module 3.2 Content-aware Reassembly Module 4 Experiments 4.1 Datasets 4.2 Bench

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1. TCP Reassembly
2. hive-the summaries of features
3. Bag-of-features-圖像檢索
4. Depth upsampling note
5. Deep Temporal Clustering: Fully unsupervised learning of time-domain features
6. Deep Clustering for Unspervised Learning of Visual Features
7. Rapid Object Detection using a Boosted Cascade of Simple Features
8. 詞袋模型（Bag of Features，BOF）
9. ASLFeat: Learning Local Features of Accurate Shape and Localization &&2020
10. List of features and minimum Clang version with support
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1. TCP Reassembly
2. hive-the summaries of features
3. Bag-of-features-圖像檢索
4. Depth upsampling note
5. Deep Temporal Clustering: Fully unsupervised learning of time-domain features
6. Deep Clustering for Unspervised Learning of Visual Features
7. Rapid Object Detection using a Boosted Cascade of Simple Features
8. 詞袋模型（Bag of Features，BOF）
9. ASLFeat: Learning Local Features of Accurate Shape and Localization &&2020
10. List of features and minimum Clang version with support

>>更多相關文章<<