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有些工作指出Transformer在图像分类上,就算扣掉很多像素,也能有很好的精度,远超CNN。 为什么你们的实验结果表明,Transformer在人脸识别任务上遮挡鲁棒性不如CNN呢? 可以解释一下吗?
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可以分享相关的论文吗?我学习一下。
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Intriguing Properties of Vision Transformers,之前看到的是这篇论文。 另外想问一下你们做遮挡人脸实验的时候,训练时没有加遮挡,只有测试的时候才会加遮挡对吧?
嗯嗯,是的,只有测试时加遮挡。
另外还想请教一下, (1) 使用adamw优化器的时候是如何找到合适的学习率的? (2) 我的做法是训练8000step, 然后看哪种学习率设置在LFW,CFP-FP测试集的准确率最高. 因为资源受限, 没办法全部训练完比较最后的准确率, 这种寻找学习率的方式合理吗?
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有些工作指出Transformer在图像分类上,就算扣掉很多像素,也能有很好的精度,远超CNN。
为什么你们的实验结果表明,Transformer在人脸识别任务上遮挡鲁棒性不如CNN呢?
可以解释一下吗?
The text was updated successfully, but these errors were encountered: