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Author Title Type [ Year(Desc)]
Filters: Author is Björn Ommer  [Clear All Filters]
2021
Kotovenko, D, Wright, M, Heimbrecht, A and Ommer, B (2021). Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://compvis.github.io/brushstroke-parameterized-style-transfer/
Roth, K, Milbich, T, Ommer, B, Cohen, J Paul and Ghassemi, M (2021). S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. Proceedings of International Conference on Machine Learning (ICML). https://arxiv.org/abs/2009.08348
Islam, M Amirul, Kowal, M, Esser, P, Jia, S, Ommer, B, Derpanis, K G and Bruce, N (2021). Shape or Texture: Understanding Discriminative Features in CNNs. International Conference on Learning Representations (ICLR)
Dorkenwald, M, Milbich, T, Blattmann, A, Rombach, R, Derpanis, K G and Ommer, B (2021). Stochastic Image-to-Video Synthesis usin cINNs. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Esser, P, Rombach, R and Ommer, B (2021). Taming Transformers for High-Resolution Image Synthesis. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://arxiv.org/abs/2012.09841
Lang, S and Ommer, B (2021). Transforming Information Into Knowledge: How Computational Methods Reshape Art History. Digital Humanities Quaterly (DHQ). 15
Lang, S and Ommer, B (2021). Transforming Information Into Knowledge: How Computational Methods Reshape Art History. Digital Humanities Quaterly (DHQ). 15. http://digitalhumanities.org/dhq/vol/15/3/000560/000560.html
Blattmann, A, Milbich, T, Dorkenwald, M and Ommer, B (2021). Understanding Object Dynamics for Interactive Image-to-Video Synthesis. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://arxiv.org/abs/2106.11303v1
Brattoli, B, Büchler, U, Dorkenwald, M, Reiser, P, Filli, L, Helmchen, F, Wahl, A - S and Ommer, B (2021). Unsupervised behaviour analysis and magnification (uBAM) using deep learning. Nature Machine Intelligence. https://rdcu.be/ch6pL

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