越線人羣計數--Crossing-line Crowd Counting with Two-phase Deep Neural Networks
Crossing-line Crowd Counting with Two-phase Deep Neural Networks ECCV2016 人羣計數有兩種做法：1） region-of-interest (ROI) 感興趣區域計數，2） line-of-interest (LOI) 感興趣線計數，就是通過圖像中某一條線的人流量。 大多數算法關注 ROI 計數問題，但是我們認爲 LOI 計數
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相關文章
- 1. Crowd Counting（人羣計數）
- 2. 人羣計數--Cross-scene Crowd Counting via Deep Convolutional Neural Networks
- 3. 快速人羣密度估計--Multi-scale Convolutional Neural Networks for Crowd Counting
- 4. 人羣計數 ICCV2019 Crowd Counting with Deep Structured Scale Integration Network （DSSINET）
- 5. 人羣計數（Crowd Counting）研究綜述
- 6. Hybrid Graph Neural Networks for Crowd Counting
- 7. 人羣計數：Single-Image Crowd Counting via Multi-Column Convolutional Neural Network(CVPR2016)
- 8. 論文理解《Dense crowd counting from still images with convolutional neural networks》
- 9. 人羣密度估計--CrowdNet: A Deep Convolutional Network for Dense Crowd Counting
- 10. 人羣計數--Switching Convolutional Neural Network for Crowd Counting