Dynamic Instance Normalization for Arbitrary Style Transfer
نویسندگان
چکیده
منابع مشابه
Supplementary Materials: Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
In Fig. 1 we show the content and style loss in training and test set. The training loss is post-processed with median filtering of window size 2000 and the test loss is computed every 2000 iterations. We did not observe much overfitting: the training and test loss trend are almost the same. We conjecture that the task is so difficult that the network with millions of parameters still underfit....
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ژورنال
عنوان ژورنال: Proceedings of the AAAI Conference on Artificial Intelligence
سال: 2020
ISSN: 2374-3468,2159-5399
DOI: 10.1609/aaai.v34i04.5862