Large Kernel Matters論文解讀
Introduction 這篇文章來自於17年的ICCV會議，作者來自清華與曠視，這篇文章提出大的卷積覈對分割網絡非常重要，並使用論文中提出的GCN（Global Convolution Network）顯著提高了分割的精度。這篇文章還有一個後續，叫做ExFuse，但ExFuse這篇文章更多的是各種小trick的疊加，質量一般。 ExFuse的論文全稱爲ExFuse: Enhancing Feat
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相關文章
- 1. Large Kernel Matters論文理解
- 2. Large Kernel Matters
- 3. Large Kernel Matters —— Improve Semantic Segmentation by Global Convolutional Network論文閱讀
- 4. Large Kernel Matters—— Improve Semantic Segmentation by Global Convolutional Network------論文理解
- 5. Large Kernel Matters ——Improve Semantic Segmentation by Global Convolutional Network論文筆記
- 6. 【論文學習記錄】Large Kernel Matters-Improve Semantic Segmentation by Global Convolutional Network
- 7. Semantic Segmentation---GCN:Large Kernel Matters---Improve Semantic Segmantic by Global ...（論文解讀四）
- 8. 圖像分割--Large Kernel matters（GCN）
- 9. 語義分割--Large Kernel Matters--Improve Semantic Segmentation by Global Convolutional Network
- 10. PaperReading4-Large Kernel Matters—— Improve Semantic Segmentation by Global Convolutional Network