Publications

Conference Proceedings

A. Blattmann, Milbich, T., Dorkenwald, M., and Ommer, B., “Behavior-Driven Synthesis of Human Dynamics”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2021.

inproceedings

T. Milbich, Roth, K., Sinha, S., Schmidt, L., Ghassemi, M., and Ommer, B., “Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning”. 2021.

Conference Paper

R. Rombach, Esser, P., and Ommer, B., “Geometry-Free View Synthesis: Transformers and no 3D Priors”, in Proceedings of the Intl. Conf. on Computer Vision (ICCV), 2021.

M. Jahn, Rombach, R., and Ommer, B., “High-Resolution Complex Scene Synthesis with Transformers”, in CVPR 2021, AI for Content Creation Workshop, 2021.

Conference Proceedings

P. Esser, Rombach, R., Blattmann, A., and Ommer, B., “ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis”. 2021.

Journal Article

A. Sanakoyeu, Ma, P., Tschernezki, V., and Ommer, B., “Improving Deep Metric Learning by Divide and Conquer”, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.

Conference Paper

A. Blattmann, Milbich, T., Dorkenwald, M., and Ommer, B., “iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis”, in Proceedings of the International Conference on Computer Vision (ICCV), 2021.

M. Afifi, Derpanis, K. G., Ommer, B., and Brown, M. S., “Learning Multi-Scale Photo Exposure Correction”, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

Conference Proceedings

D. Kotovenko, Wright, M., Heimbrecht, A., and Ommer, B., “Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2021.

K. Roth, Milbich, T., Ommer, B., Cohen, J. Paul, and Ghassemi, M., “S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning”, Proceedings of International Conference on Machine Learning (ICML). 2021.

M. Amirul Islam, Kowal, M., Esser, P., Jia, S., Ommer, B., Derpanis, K. G., and Bruce, N., “Shape or Texture: Understanding Discriminative Features in CNNs”, International Conference on Learning Representations (ICLR). 2021.

M. Dorkenwald, Milbich, T., Blattmann, A., Rombach, R., Derpanis, K. G., and Ommer, B., “Stochastic Image-to-Video Synthesis usin cINNs”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2021.

P. Esser, Rombach, R., and Ommer, B., “Taming Transformers for High-Resolution Image Synthesis”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2021.

Journal Article

S. Lang and Ommer, B., “Transforming Information Into Knowledge: How Computational Methods Reshape Art History”, Digital Humanities Quaterly (DHQ), vol. 15, no. 3, 2021.

Conference Proceedings

A. Blattmann, Milbich, T., Dorkenwald, M., and Ommer, B., “Understanding Object Dynamics for Interactive Image-to-Video Synthesis”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2021.

Journal Article

B. Brattoli, Büchler, U., Dorkenwald, M., Reiser, P., Filli, L., Helmchen, F., Wahl, A. - S., and Ommer, B., “Unsupervised behaviour analysis and magnification (uBAM) using deep learning”, Nature Machine Intelligence, 2021.

Conference Proceedings

S. Lang and Ommer, B., “Das Objekt jenseits der Digitalisierung”, Das digitale Objekt, vol. 7. 2020.

lang_ommer_digitalhumanities_2020_.pdf (599.56 KB)

Journal Article

T. Dencker, Klinkisch, P., Maul, S. M., and Ommer, B., “Deep learning of cuneiform sign detection with weak supervision using transliteration alignment”, PLoS ONE, vol. 15, no. 12, 2020.

Conference Proceedings

P. Esser, Rombach, R., and Ommer, B., “A Disentangling Invertible Interpretation Network for Explaining Latent Representations”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2020.

Article (13.07 MB)

T. Milbich, Roth, K., Bharadhwaj, H., Sinha, S., Bengio, Y., Ommer, B., and Cohen, J. Paul, “DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning”, IEEE European Conference on Computer Vision (ECCV). 2020.

R. Rombach, Esser, P., and Ommer, B., “Making Sense of CNNs: Interpreting Deep Representations & Their Invariances with INNs”, IEEE European Conference on Computer Vision (ECCV). 2020.

Conference Paper

R. Rombach, Esser, P., and Ommer, B., “Network Fusion for Content Creation with Conditional INNs”, in CVPRW 2020 (AI for Content Creation), 2020.

Conference Proceedings

R. Rombach, Esser, P., and Ommer, B., “Network-to-Network Translation with Conditional Invertible Neural Networks”, Neural Information Processing Systems (NeurIPS) (Oral). 2020.

Conference Paper

P. Esser, Rombach, R., and Ommer, B., “A Note on Data Biases in Generative Models”, in NeurIPS 2020 Workshop on Machine Learning for Creativity and Design, 2020.

Conference Proceedings

N. Ufer, Lang, S., and Ommer, B., “Object Retrieval and Localization in Large Art Collections Using Deep Multi-style Feature Fusion and Iterative Voting”, IEEE European Conference on Computer Vision (ECCV), VISART Workshop . 2020.

Paper (1.03 MB)

Conference Paper

T. Milbich, Roth, K., and Ommer, B., “PADS: Policy-Adapted Sampling for Visual Similarity Learning”, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020, vol. 1, no. 1.

Conference Proceedings

K. Roth, Milbich, T., Sinha, S., Gupta, P., Ommer, B., and Cohen, J. Paul, “Revisiting Training Strategies and Generalization Performance in Deep Metric Learning”, International Conference on Machine Learning (ICML). 2020.

Journal Article

T. Milbich, Roth, K., Brattoli, B., and Ommer, B., “Sharing Matters for Generalization in Deep Metric Learning”, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.

Conference Proceedings

M. Dorkenwald, Büchler, U., and Ommer, B., “Unsupervised Magnification of Posture Deviations Across Subjects”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2020.

article.pdf (1.15 MB)

S. Braun, Esser, P., and Ommer, B., “Unsupervised Part Discovery by Unsupervised Disentanglement”, Proceedings of the German Conference on Pattern Recognition (GCPR) (Oral). Tübingen, 2020.

Journal Article

T. Milbich, Ghori, O., and Ommer, B., “Unsupervised Representation Learning by Discovering Reliable Image Relations”, Pattern Recognition, vol. 102, 2020.

Conference Paper

D. Kotovenko, Sanakoyeu, A., Lang, S., and Ommer, B., “Content and Style Disentanglement for Artistic Style Transfer”, in Proceedings of the Intl. Conf. on Computer Vision (ICCV), 2019.

Conference Proceedings

A. Sanakoyeu, Tschernezki, V., Büchler, U., and Ommer, B., “Divide and Conquer the Embedding Space for Metric Learning”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2019.

Conference Paper

B. Brattoli, Roth, K., and Ommer, B., “MIC: Mining Interclass Characteristics for Improved Metric Learning”, in Proceedings of the Intl. Conf. on Computer Vision (ICCV), 2019.

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