Have you ever wondered how your face would look as a whimsical cartoon or how you could magically change your hair color in a photograph? The cutting-edge technology we're about to explore can make those dreams a reality and take your images to dazzling new heights! 🎨🚀
This most recent video is about a revolutionary AI architecture known as StyleGANEX. Developed by brilliant researchers and showcased at ICCV 2023, StyleGANEX is all about pushing boundaries and shattering limitations.
No more settling for pixelated or low-res images! StyleGANEX elegantly tackles the challenges of flexible input sizes, allowing you to transform any image into a stunning work of art without compromising on quality. 🌈 And the best thing about it is that their code is fully open-source, and they have a demo available online (all links in the video description)!
Obviously, the architecture is mostly based on StyleGAN, which has lots of pre-trained models you can play with, but all have this input image size issue we discussed, which ends up producing different encodings in the latent space too since they all follow the same convolutions.
So, everything is of different sizes based on the image you want to process.
Here, the researchers did a simple fix to this issue by implementing a dilated convolution to rescale the receptive fields of shallow layers in the StyleGAN generator architecture. But what does this mean?
I'll guide you through the power of dilated convolutions, the wizardry that makes StyleGANEX an absolute game-changer in the world of AI image editing. And the best part? You don't need to be a tech expert to understand it all! 🧙🎓
Don't miss out – hit that play button and immerse yourself in the magic of StyleGANEX. And hey, if you're attending ICCV 2023 in Paris, we might cross paths! 🗼
►Read the full article: https://www.louisbouchard.ai/styleganex/
►Demo: https://huggingface.co/spaces/PKUWilliamYang/StyleGANEX
►Paper: https://arxiv.org/abs/2303.06146
►Code: https://github.com/williamyang1991/StyleGANEX
►Project page: https://www.mmlab-ntu.com/project/styleganex/
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