Comments (1)
As mentioned in Section 4.1.2, to decode the 2D prediction, we flattened the 2D prediction
by concatenating each column in order from left to right and top to bottom and then decoded the flattened 1D prediction following the general procedure.
from aggregation-cross-entropy.
Related Issues (20)
- Would it be helpful in Speech Recognition especially in acoustic model to replace CTC with ACE? HOT 1
- Do ACE work? same point about HCTR Result
- Prediction script HOT 2
- Why use ResLSTM for Offline Handwritten Chinese Text Recognition ? HOT 1
- Use ACE loss for English handwriting recognition,but not converge HOT 2
- KL Divergence
- Could you share your trained models?
- Can’t reproduce your results in your cvpr paper HOT 3
- Compared with CTC, the effect is very poor in Chinese long text
- combined with CTC? HOT 1
- It doesn't work on my data, why don't you provide a pretrained model? HOT 5
- Would MSE loss work if i remove the softmax?
- What is the accuracy criterion in 2D prediction?
- def vis(self,iteration) function, possible error
- 关于论文公式(2)的理解问题
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- HWDB results
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- I would like to ask you how to accurately predict the character order of a word. HOT 6
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from aggregation-cross-entropy.