NVIDIA AI Research in Action

AI and deep learning is serious business at NVIDIA, but that doesn’t mean you can’t have a ton of fun putting it to work. Researchers at NVIDIA challenge themselves each day to answer the “what ifs” that push deep learning architectures and algorithms to richer practical applications. See some of that work in these fun, intriguing, artful and surprising projects.



GauGAN, named after post-Impressionist painter Paul Gauguin, creates photorealistic images from segmentation maps, which are labeled sketches that depict the layout of a scene.

Artists can use paintbrush and paint bucket tools to design their own landscapes with labels like river, rock and cloud. A style transfer algorithm allows creators to apply filters — changing a daytime scene to sunset, or a photorealistic image to a painting. Users can even upload their own filters to layer onto their masterpieces, or upload custom segmentation maps and landscape images as a foundation for their artwork

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Image Inpainting

Step right up and see deep learning inference in action on your very own portraits or landscapes. Our researchers developed state-of-the-art image reconstruction that fills in missing parts of an image with new pixels that are generated from the trained model, independent from what’s missing in the photo. Give it a shot with a landscape or portrait. Erase at will — get rid of that photobomber, or your ex, and then see what happens when new pixels are painted into the holes.

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Image Inpainting


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