I was impressed with the Labeled Faces in the Wild (LFW) facial auto-completion results, especially since the system was not trained on LFW at all! The results seemed almost too good to be true. Perhaps this is a testament that there isn't that much diversity in human faces?
Very well written overall, and I appreciated the author's thoughts on TensorFlow+torch at the end of the article.
Adversarial training is a fascinating idea, and I love the sound of it. I'd like to start applying that concept in the future.
Awesome! Could use this technique to create a personal version of Google photos (thinking specifically of their automatic generation of albums of 'sunsets' or 'dogs').
It would be cool if you could use a GAN to generate images merely by providing an object name. You could train the GAN on images obtained by searching for that object name in an image search engine.
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[ 2.8 ms ] story [ 44.3 ms ] threadVery well written overall, and I appreciated the author's thoughts on TensorFlow+torch at the end of the article.
Adversarial training is a fascinating idea, and I love the sound of it. I'd like to start applying that concept in the future.
http://www.pyimagesearch.com/2016/08/10/imagenet-classificat...
Uses TF deep learning to classify an image.