论文理解《Stacked Pooling: Improving Crowd Counting by Boosting Scale Invariance》

时间 2021-01-13

标签 crowd count scale invariance 栏目 C&C++ 繁體版

原文原文链接

代码主页：https://github.com/siyuhuang/crowdcount-stackpool 解决问题：在池化层上下功夫，解决了图像处理中的多尺度问题；发现： 1.在人群计数的图片数据集上，如果将不同区域的图片resize到一定的尺寸，这两个区域会表现出极大的视觉相似性（包括人物大小、人群密度、层叠关系）；见下图。 2. a larger pooling range enable

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1. 论文理解《Body Structure Aware Deep Crowd Counting》
2. 论文理解Leveraging Unlabeled Data for Crowd Counting by Learning to Rank
3. 《Crowd Counting via Adversarial Cross-Scale Consistency Pursuit》解读
4. Multi-Source Multi-Scale Counting in Extremely Dense Crowd Images(CVPR2013)——论文笔记
5. Scale-Aware Attention Network for Crowd Counting 论文笔记
6. 《Multi-scale Convolutional Neural Networks for Crowd Counting》论文笔记
7. (论文笔记2019ICCV) Learn to Scale: Generating Multipolar Normalized Density Maps for Crowd Counting
8. 论文理解《Class-Agnostic Counting》
9. 论文解读《CrowdNet: A Deep Convolutional Network for Dense Crowd Counting》ACMM-MM2016
10. [论文笔记 CVPR2020]Attention Scaling for Crowd Counting

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