深度监督对齐的零样本图像分类方法
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曾素佳,庞善民,郝问裕
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Zero-shot image classification method base on deep supervised alignment
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Su-jia ZENG,Shan-min PANG,Wen-yu HAO
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表 2 不同数据集上传统零样本分类准确率表现对比1) |
Tab.2 Comparison of performance for ZSL on different dataset % |
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方法 | A | CUB | AWA1 | AWA2 | SUN | APY | 1)注:带“*”的实验数据由文献作者公开的源代码复现得到;“−”代表未测;表中其他算法的数据来自文献[21]公开的复现结果. | SAE[25] | 33.3 | 53.0 | 54.1 | 40.3 | 8.3 | CDL[7] | 54.5 | 69.9 | − | 63.6 | 43.0 | GAZSL[15] | 55.8 | 68.2 | 70.2 | 61.3 | 41.1 | DCN[16] | 56.2 | 65.2 | − | 61.8 | 43.6 | f-CLSWGAN[18] | 57.3 | 68.2 | − | 60.8 | − | FD-fGAN[19] | 58.3 | 72.6 | − | 61.5 | − | Rnet[6] | 55.6 | 68.2 | 64.2 | 49.3* | 39.8* | SARN[8] | 53.8 | 68.0 | 64.2 | − | − | TCN[10] | 59.5 | 70.3 | 71.2 | 61.5 | 38.9 | CRnet[11] | 56.6* | 69.1* | 63.0* | 61.4* | 39.1* | DSAN | 57.4 | 71.8 | 72.3 | 62.4 | 41.5 |
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