Large Kernel Matters论文解读
Introduction 这篇文章来自于17年的ICCV会议，作者来自清华与旷视，这篇文章提出大的卷积核对分割网络非常重要，并使用论文中提出的GCN（Global Convolution Network）显著提高了分割的精度。这篇文章还有一个后续，叫做ExFuse，但ExFuse这篇文章更多的是各种小trick的叠加，质量一般。 ExFuse的论文全称为ExFuse: Enhancing Feat
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相关文章
- 1. Large Kernel Matters论文理解
- 2. Large Kernel Matters
- 3. Large Kernel Matters —— Improve Semantic Segmentation by Global Convolutional Network论文阅读
- 4. Large Kernel Matters—— Improve Semantic Segmentation by Global Convolutional Network------论文理解
- 5. Large Kernel Matters ——Improve Semantic Segmentation by Global Convolutional Network论文笔记
- 6. 【论文学习记录】Large Kernel Matters-Improve Semantic Segmentation by Global Convolutional Network
- 7. Semantic Segmentation---GCN:Large Kernel Matters---Improve Semantic Segmantic by Global ...（论文解读四）
- 8. 图像分割--Large Kernel matters（GCN）
- 9. 语义分割--Large Kernel Matters--Improve Semantic Segmentation by Global Convolutional Network
- 10. PaperReading4-Large Kernel Matters—— Improve Semantic Segmentation by Global Convolutional Network