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bug information :
Epoch: 0, LR: [0.1]
Train set: 196, Train Loss: 3.4775 Acc: 9.5960
/opt/conda/conda-bld/pytorch_1556653215914/work/aten/src/THCUNN/ClassNLLCriterion.cu:105: void cunn_ClassNL…
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每天进步一点点
记录每天学到了什么吧
还有找到的非常棒的资料都会记录在这里
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I read your paper and I think this is really inspiring work. I really hope to try the model and test some ideas. So I'm wondering whether/when will the code or model described in paper be released?
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Please take a look at https://github.com/ChaofWang/Awesome-Super-Resolution and https://github.com/YapengTian/Single-Image-Super-Resolution for other algorithms that you can implement in order to be c…
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Thank you for sharing this wonderful code first!
And I have a small question in discriminator.I find the adversarial loss of AdaptSegNet is very unstable because of the global alignment in the segme…
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thanks for your great work.
could i ask that what i should do to test this model on my own dataset?
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Hi,
Will you provide the training code to replicate the results from the paper and generate the frozen Tensorflow graph model?
Thanks
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Hello,
Can you please share RailSem 19 dataset? I applied for downloading the dataset around two weeks ago, but I haven't received any reply till now.
Thank you.
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I am using cvpr19 branch, cuda10.0, pytorch 1.1.0, and windows11
I downloaded trained model and smplx model from smplify-x repo
For my case I cannot run any of given jupyter tutorial
from bel…