Yuntian Deng
Yuntian Deng
The paper can be found here: https://arxiv.org/abs/1609.04938v1. We didn't publish our results on traditional tasks like SVHN tho.
Hi @ganliqiang, "image-to-markup generation with coarse-to-fine attention" is just an updated version of "what you get is what you see". However, coarse-to-fine attention is not implemented in this repo, so...
Thanks for the feedback! Do you have a detailed error message? And actually I was testing on the latest tensorflow (0.11).
Sorry I didn't quite get it. What do you mean by bias terms?
I see. Yes you're right, since we apply batch norm before ReLU's, anyway the features are recentered such that bias terms are not needed.
Hi sorry we don't have the icdar training data since we did this project three years ago...
Yes. If you are setting that flag to 1 during test phase, it basicaly means when you receive a test batch, you are doing the same thing as in training:...
It's cross-entropy loss, same as in other sequence prediction tasks such as translation.
Not sure if this would help, but I encountered the same issue and had to rollback to an earlier version of apex: ``` git checkout f3a960f80244cf9e80558ab30f7f7e8cbf03c0a0 ```
Hmm I suspect there's something wrong with your cutorch. Can you try `th -lcutorch -e "cutorch.test()"` and see the results?