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A team of scientists has presented a new resolution-robust Large Mask Inpainting with Fourier Convolutions, or LaMa for short. LaMa can be used to remove various objects from pictures like people, furniture, buildings, animals, not-needed details, etc. The network then recreates the background behind the deleted objects and achieves excellent performance even in challenging scenarios, e.g. completion of periodic structures.
"Our inpainting network improves the state-of-the-art across a range of datasets and achieves excellent performance even in challenging scenarios, e.g.completion of periodic structures. Our model generalizes surprisingly well to resolutions that are higher than those seen at train time, and achieves this at lower parameter & compute costs than the competitive baselines," comments the team.
You can learn more about LaMa here and try the network here. Also, don't forget to join our new Reddit page, our new Telegram channel, follow us on Instagram and Twitter, where we are sharing breakdowns, the latest news, awesome artworks, and more.
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