SGE——Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional Networks
这篇文章借鉴了SEnet，然后做了结构的改动。 作者提到，一个完整的feature是由许多sub feature组成的，并且这些sub feature会以group的形式分布在每一层的feature里，但是这些子特征会经由相同方式处理，且都会有背景噪声影响。这样会导致错误的识别和定位结果。所以作者提出了SGE模块，它通过在在每个group里生成attention factor，这样就能得到每个su
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相关文章
- 1. Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional Network
- 2. Fully Convolutional Adaptation Networks for Semantic Segmentation
- 3. Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
- 4. Improving Facial Attribute Prediction using Semantic Segmentation, in arxiv 2017.04
- 5. 【论文翻译】Fully Convolutional Networks for Semantic Segmentation_2
- 6. 【论文翻译】Fully Convolutional Networks for semantic Segmentation
- 7. 【论文翻译】Fully Convolutional Networks for Semantic Segmentation
- 8. Fully Convolutional Networks for Semantic Segmentation 全文翻译
- 9. SCA-CNN: Spatial and Channel-wise Attention in Convolutional Networks for Image Captioning
- 10. Fully Convolutional Networks for Semantic Segmentation