Zobrazeno 1 - 10
of 94
pro vyhledávání: '"Lorenz, Dominik"'
Autor:
Esser, Patrick, Kulal, Sumith, Blattmann, Andreas, Entezari, Rahim, Müller, Jonas, Saini, Harry, Levi, Yam, Lorenz, Dominik, Sauer, Axel, Boesel, Frederic, Podell, Dustin, Dockhorn, Tim, English, Zion, Lacey, Kyle, Goodwin, Alex, Marek, Yannik, Rombach, Robin
Diffusion models create data from noise by inverting the forward paths of data towards noise and have emerged as a powerful generative modeling technique for high-dimensional, perceptual data such as images and videos. Rectified flow is a recent gene
Externí odkaz:
http://arxiv.org/abs/2403.03206
By decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image data and beyond. Additionally, their formulation allows for a guiding mecha
Externí odkaz:
http://arxiv.org/abs/2112.10752
Large intra-class variation is the result of changes in multiple object characteristics. Images, however, only show the superposition of different variable factors such as appearance or shape. Therefore, learning to disentangle and represent these di
Externí odkaz:
http://arxiv.org/abs/1903.06946
Akademický článek
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Autor:
Schneider Julian, Forster Patrick, Panitzek Dieter, Lorenz Dominik, Romano Clément, Eichhorn Marc, Kieleck Christelle
Publikováno v:
EPJ Web of Conferences, Vol 267, p 02004 (2022)
Externí odkaz:
https://doaj.org/article/1964a80a8ecc487abbdb9732f766184d
Autor:
Lorenz Dominik, Romano Clément, Panitzek Dieter, Forster Patrick, Schneider Julian, Eichhorn Marc, Kieleck Christelle
Publikováno v:
EPJ Web of Conferences, Vol 267, p 02006 (2022)
Externí odkaz:
https://doaj.org/article/ad59fa9fac6c4a43a52c1263dd937082
Autor:
Romano Clément, Panitzek Dieter, Lorenz Dominik, Forster Patrick, Eichhorn Marc, Kieleck Christelle
Publikováno v:
EPJ Web of Conferences, Vol 267, p 02016 (2022)
Externí odkaz:
https://doaj.org/article/94765d1688c44ea585edfb2dd142803e
Autor:
Hüppe, Tobias1 (AUTHOR), Lorenz, Dominik1 (AUTHOR), Maurer, Felix1 (AUTHOR), Fink, Tobias1 (AUTHOR), Klumpp, Ramona1 (AUTHOR), Kreuer, Sascha1 (AUTHOR)
Publikováno v:
Journal of Analytical Methods in Chemistry. 8/3/2021, p1-6. 6p.
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
By decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image data and beyond. Additionally, their formulation allows for a guiding mecha