基于能量模型的行人与车辆再识别方法
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张师林,郭红南,刘轩
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Person and vehicle re-identification based on energy model
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Shi-lin ZHANG,Hong-nan GUO,Xuan LIU
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| 表 3 在3个行人再识别数据集上与同类方法的Rank1 和mAP指标对比 |
| Tab.3 Rank1 and mAP performance comparison with state of art methods on three person re-ID datasets |
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| % | | 方法 | Market1501 | | DukeMTMC-ReID | | MSMT | | Rank1 | mAP | Rank1 | mAP | Rank1 | mAP | | Camstyle[19] | 88.1 | 68.7 | | 75.3 | 53.5 | | — | — | | PN-GAN[20] | 89.4 | 72.6 | 73.6 | 53.2 | — | — | | MGN[21] | 95.7 | 86.9 | 88.7 | 78.4 | — | — | | Pyramid[22] | 95.7 | 88.2 | 89.0 | 79.0 | — | — | | ABD-Net[23] | 95.6 | 88.3 | 88.3 | 78.6 | — | — | | PCB[24] | 93.8 | 81.6 | 83.3 | 69.2 | 68.2 | 40.4 | | SPReID[25] | 92.5 | 81.3 | 84.4 | 71.0 | — | — | | MaskReID[26] | 90.0 | 75.3 | 78.8 | 61.9 | — | — | | SCPNet[27] | 91.2 | 75.2 | 80.3 | 62.6 | — | — | | HA-CNN[28] | 91.2 | 75.7 | 80.5 | 63.8 | — | — | | SVDNet[29] | 82.3 | 62.1 | 76.7 | 56.8 | — | — | | TransReID[30] | 95.2 | 89.5 | 91.1 | 82.1 | 86.20 | 69.4 | | Energy-Loss | 95.9 | 89.9 | 92.3 | 83.5 | 85.52 | 70.9 |
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