LatentCLR: A Contrastive Learning Approach for Unsupervised Discovery of Interpretable Directions
A framework that learns meaningful directions in GANs' latent space using unsupervised contrastive learning. Instead of discovering fixed directions such as in previous work, this method can discover non-linear directions in pretrained StyleGAN2 and BigGAN models. The discovered directions may be used for image manipulation.
Authors use the differences caused by an edit operation on the feature activations to optimize the identifiability of each direction. The edit operations are modeled by several separate neural nets
📝 Paper
🛠 Code (next week)
#paper_tldr #cv #gan
A framework that learns meaningful directions in GANs' latent space using unsupervised contrastive learning. Instead of discovering fixed directions such as in previous work, this method can discover non-linear directions in pretrained StyleGAN2 and BigGAN models. The discovered directions may be used for image manipulation.
Authors use the differences caused by an edit operation on the feature activations to optimize the identifiability of each direction. The edit operations are modeled by several separate neural nets
∆_i(z) and learning. Given a latent code z and its generated image x = G(z), we seek to find edit operations ∆_i(z) such that the image x' = G(∆_i(z)) has semantically meaningful changes over x while still preserving the identity of x.📝 Paper
🛠 Code (next week)
#paper_tldr #cv #gan
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Spectacular Image Stylization using CLIP and DALL-E
As a Style Transfer Dude, I can say that this is super cool. A statue of David by Michelangelo was used as an input image. Then it was morphed towards different styles of famous artists by steering the latent code towards the embeddings of a textual description in CLIP space.
I especially like Picasso's Cubism where it created a half-bull half-human portrait which is one of the typical sujets of Picasso. Rene Magritte's stylization is my second favorite.
I discussed similar techniques for image editing here and here.
📙Colab which contains the most significant parts to reproduce the results: link.
Original youtube video.
Thanks @NeuralShit for the pointer.
#image_gen #gan #style_transfer
As a Style Transfer Dude, I can say that this is super cool. A statue of David by Michelangelo was used as an input image. Then it was morphed towards different styles of famous artists by steering the latent code towards the embeddings of a textual description in CLIP space.
I especially like Picasso's Cubism where it created a half-bull half-human portrait which is one of the typical sujets of Picasso. Rene Magritte's stylization is my second favorite.
I discussed similar techniques for image editing here and here.
📙Colab which contains the most significant parts to reproduce the results: link.
Original youtube video.
Thanks @NeuralShit for the pointer.
#image_gen #gan #style_transfer