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The paper introduces HyperDreamBooth, a hypernetwork that efficiently generates personalized weights from a single image, enabling fast and high-quality face synthesis in various styles and contexts. It achieves personalization 25x faster than DreamBooth and yields a much smaller model.
https://arxiv.org/abs//2307.06949
YouTube: https://www.youtube.com/@ArxivPapers
PODCASTS:
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
By Igor Melnyk5
33 ratings
The paper introduces HyperDreamBooth, a hypernetwork that efficiently generates personalized weights from a single image, enabling fast and high-quality face synthesis in various styles and contexts. It achieves personalization 25x faster than DreamBooth and yields a much smaller model.
https://arxiv.org/abs//2307.06949
YouTube: https://www.youtube.com/@ArxivPapers
PODCASTS:
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers

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