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您好,非常感谢您的工作!我想在自己的数据集上重新训练您开源的方法,请问ResNet18的预训练是指High-frequency图像域的适配么,您用了什么方式监督这个训练?OCR的模型也是为了适应VAE encode之后的图像域嘛?
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您好~ResNet18我们直接使用了VATr提供的预训练模型,OCR模型是在latent code上预训练的。用vae把图像编码到latet space,然后使用ctc loss优化OCR模型。
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感谢回复!如果我没有记错的话,VATr所预训练的R18使用了他们团队自己的Font^{2}(Evaluating Synthetic Pre-Training for Handwriting Processing Tasks)方法,不过放出的模型参数中似乎并没有中文数据的加入。不知道您在训练中文版本的模型时,直接使用VATr提供的参数会不会影响其泛化性?或者说如果能有中文分布的数据训练R18,对风格的提取和文字的生成效果会更好一些,您有相关的实验嘛~
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您好,非常感谢您的工作!我想在自己的数据集上重新训练您开源的方法,请问ResNet18的预训练是指High-frequency图像域的适配么,您用了什么方式监督这个训练?OCR的模型也是为了适应VAE encode之后的图像域嘛?
The text was updated successfully, but these errors were encountered: