論文理解《Dense crowd counting from still images with convolutional neural networks》
論文《Dense crowd counting from still images with convolutional neural networks》 創新點：使用深度學習方法估計一張圖片中中等、高度擁塞程度的人羣； 解決問題： 人羣計數算法的一些侷限性： （1）當人羣規模達到成百上千時，這些算法只能用來估計人羣密度而不能計算人羣總數；（2）通常依賴於人羣視頻中的時序，但是這點
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相關文章
- 1. 論文解讀《CrowdNet: A Deep Convolutional Network for Dense Crowd Counting》ACMM-MM2016
- 2. 《Multi-scale Convolutional Neural Networks for Crowd Counting》論文筆記
- 3. Multi-Source Multi-Scale Counting in Extremely Dense Crowd Images(CVPR2013)——論文筆記
- 4. 論文解析 - SemanticFusion: Dense 3D Semantic Mapping with Convolutional Neural Networks
- 5. Inverting Convolutional Networks with Convolutional Networks 論文理解
- 6. Hybrid Graph Neural Networks for Crowd Counting
- 7. 論文解讀《Almost Unsupervised Learning for Dense Crowd Counting》AAAI2019
- 8. ImageNet Classification with Deep Convolutional Neural Networks
- 9. 越線人羣計數--Crossing-line Crowd Counting with Two-phase Deep Neural Networks
- 10. Crowd Counting（人羣計數）