Semantic Pyramid for Image Generation
This video explores a new GAN model for generating images by conditioning them on features from pre-trained image classifiers! This is really interesting for visualizing what is contained in pre-trained image classifiers as well as controllable image editing. The authors also show that this can be used for semantic image composition such as copying a tree and pasting it into a snow landscape or image relabeling by changing the embedded logit from the pre-trained classifier to produce an image of a new class while retaining as much of the original image as possible.
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Paper Links:
Semantic Pyramid for Image Generation: https://arxiv.org/abs/2003.06221
Corresponding Github Page: https://semantic-pyramid.github.io/su...
Neural Style Transfer: https://arxiv.org/pdf/1508.06576.pdf
Zoom In: An Introduction to Circuits: https://distill.pub/2020/circuits/zoo...
EfficientDet: https://arxiv.org/pdf/1911.09070.pdf
Generative Teaching Networks: https://arxiv.org/pdf/1912.07768.pdf
DermGAN: https://arxiv.org/pdf/1911.08716.pdf
Classification Accuracy Score for Conditional Generative Models: https://arxiv.org/pdf/1905.10887.pdf
GauGAN: https://arxiv.org/pdf/1903.07291.pdf
SinGAN: https://arxiv.org/pdf/1905.01164.pdf
StyleGAN2 Distillation: https://arxiv.org/pdf/2003.03581.pdf
Semi-Supervised StyleGAN for Disentanglement Learning: https://arxiv.org/pdf/2003.03461.pdf
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Watch video Semantic Pyramid for Image Generation online without registration, duration hours minute second in high quality. This video was added by user Connor Shorten 18 March 2020, don't forget to share it with your friends and acquaintances, it has been viewed on our site 1,809 once and liked it 65 people.