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Author [ Title(Desc)] Type Year
Filters: Author is Robin Rombach  [Clear All Filters]
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D
Esser, P, Rombach, R and Ommer, B (2020). A Disentangling Invertible Interpretation Network for Explaining Latent Representations. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://compvis.github.io/iin/PDF icon Article (13.07 MB)
G
Rombach, R, Esser, P and Ommer, B (2021). Geometry-Free View Synthesis: Transformers and no 3D Priors. Proceedings of the Intl. Conf. on Computer Vision (ICCV). https://arxiv.org/abs/2104.07652
H
Jahn, M, Rombach, R and Ommer, B (2021). High-Resolution Complex Scene Synthesis with Transformers. CVPR 2021, AI for Content Creation Workshop
I
Esser, P, Rombach, R, Blattmann, A and Ommer, B (2021). ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis. https://arxiv.org/abs/2108.08827
M
Rombach, R, Esser, P and Ommer, B (2020). Making Sense of CNNs: Interpreting Deep Representations & Their Invariances with INNs. IEEE European Conference on Computer Vision (ECCV). https://compvis.github.io/invariances/
N
Rombach, R, Esser, P and Ommer, B (2020). Network Fusion for Content Creation with Conditional INNs. CVPRW 2020 (AI for Content Creation). https://compvis.github.io/network-fusion/
Rombach, R, Esser, P and Ommer, B (2020). Network-to-Network Translation with Conditional Invertible Neural Networks. Neural Information Processing Systems (NeurIPS) (Oral). https://compvis.github.io/net2net/
Esser, P, Rombach, R and Ommer, B (2020). A Note on Data Biases in Generative Models. NeurIPS 2020 Workshop on Machine Learning for Creativity and Design. https://arxiv.org/abs/2012.02516
S
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)
T
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