阅读《Detecting Faces Using Inside Cascaded Contextual CNN》的理解
Detecting Faces Using Inside Cascaded Contextual CNN 这篇文章出自2017的ICCV，文章链接。其主要的贡献在两个地方：1、高层的卷积核区分复杂的负样本的能力更强，而简单的负样本在低层就可以检测出来，不用传入到后面的网络层去区分，这样既可以减少高层的计算量来节约时间，同时也可以让高层的卷积核集中于解决复杂的正负样本。所以该篇文章
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相关文章
- 1. 级联人脸检测--Detecting Faces Using Inside Cascaded Contextual CNN
- 2. Detecting and counting tiny faces
- 3. Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks阅读笔记
- 4. 【论文阅读】Finding Tiny Faces
- 5. 论文阅读：Detecting Visual Relationships Using Box Attention
- 6. 人脸检测--Grid Loss: Detecting Occluded Faces
- 7. 论文阅读：Detecting and Recognizing Human-Object Interactions
- 8. Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks（MTCNN）论文和代码解读
- 9. Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks论文理解
- 10. 【论文浅读】《Generating High-Quality Crowd Density Maps Using Contextual Pyramid CNNs》