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Hi! For all the DL libraries out there, as well as the image processing packages it would make sense to have GPU-powered upsampling (nearest, bilinear, cubic), including their derivatives. Being able …
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Thanks for your work on getting ENet in Keras! Have you found any increases in accuracy from using MaxUnpooling instead of just naive UpSampling?
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Can I let's say, upsample half of the generated sample on one day, and then continue from the checkpoint and do the other half on the next day?
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Hi, I'd like to train the network on a, 8x down-sampled input/full resolution reference, data set. Is this possible? What modifications are necessary. Thanks a lot.
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In `model/deconv_head.py`, I only found the bilinear upsampling, I searched the keyword `deformable` but found nothing.
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For the aggregated cost volume, we show the output of our model, hence has a higher resolution of 96x96. We simply apply bilinear upsampling to overlay with the image.
I don't have the code at the …
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Upsampling is a common practice for unbalanced data sets. The best practice for upsampling is to upsample the training set AFTER splitting into train and test sets, because if you duplicate rows befor…
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The existing Upsampling operator supports only one integer scale.
It would be useful to have this as a list of floats - a different scale per dimension.
This is required with ONNX export/import…
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According to the description linear upsampling is not supposed to depend on the number of filters. However the default value results in a segfault and setting a number not equal to the number of filte…
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Is it possible without too much resources?