基于自注意力机制的双分支密集人群计数算法
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杨天乐,李玲霞,张为
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Dual-branch crowd counting algorithm based on self-attention mechanism
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Tian-le YANG,Ling-xia LI,Wei ZHANG
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| 表 2 计数级-弱监督对比实验的结果 |
| Tab.2 Results of count-level weakly supervision comparison experiment |
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| 算法 | SHT Part A | | SHT Part B | | UCF_QNRF | | UCF_CC_50 | | JHU-Crowd++ | | MAE | MSE | MAE | MSE | MAE | MSE | MAE | MSE | MAE | MSE | | Yang[34] | 104.6 | 145.2 | | 12.3 | 21.2 | | — | — | | — | — | | — | — | | MATT[15] | 80.1 | 129.4 | 11.7 | 17.5 | — | — | 355.0 | 550.2 | — | — | | TDCrowd[35] | 67.9 | 108.3 | — | — | — | — | — | — | — | — | | TransCrowd[16] | 66.1 | 105.1 | 9.3 | 16.1 | 97.2 | 168.5 | — | — | 74.9 | 595.6 | | CCST[36] | 62.8 | 94.1 | 8.3 | 13.4 | 93.7 | 166.9 | 190.7 | 289.0 | 61.4 | 239.3 | | DBCC-Net | 60.1 | 94.0 | 7.5 | 12.5 | 90.9 | 156.3 | 177.1 | 237.9 | 61.3 | 241.8 |
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