Discovering optical control strategies : a data-mining approach. - Romann M. Weber (2013)

InspireMe: Learning Sequence Models for Stories. - Vincent Fortuin; Romann M. Weber; Sasha Schriber; Diana Wotruba; Markus H. Gross (AAAI, 2018)

Unsupervised Deep Representations for Learning Audience Facial Behaviors. - Suman Saha; Rajitha Navarathna; Leonhard Helminger; Romann M. Weber (CVPR Workshops, 2018)

Disentangled Dynamic Representations from Unordered Data. - Leonhard Helminger; Abdelaziz Djelouah; Markus H. Gross; Romann M. Weber (CoRR, 2018)

High-Resolution Neural Face Swapping for Visual Effects. - Jacek Naruniec; Leonhard Helminger; Christopher Schroers; Romann M. Weber (Comput. Graph. Forum, 2020)

The Hidden Tasks of Generative Adversarial Networks: An Alternative Perspective on GAN Training. - Romann M. Weber (CoRR, 2021)

Deep Adaptive Sampling and Reconstruction Using Analytic Distributions. - Farnood Salehi; Marco Manzi; Gerhard Roethlin; Romann M. Weber; Christopher Schroers; Marios Papas (ACM Trans. Graph., 2022)

Learning Dynamic 3D Geometry and Texture for Video Face Swapping. - Christopher Otto; Jacek Naruniec; Leonhard Helminger; Thomas Etterlin; Graziana Mignone; Prashanth Chandran; Gaspard Zoss; Christopher Schroers; Markus Gross 001; Paulo F. U. Gotardo; Derek Bradley; Romann M. Weber (Comput. Graph. Forum, 2022)

Controllable Inversion of Black-Box Face Recognition Models via Diffusion. - Manuel Kansy; Anton Raël; Graziana Mignone; Jacek Naruniec; Christopher Schroers; Markus Gross 001; Romann M. Weber (ICCV (Workshops), 2023)

Memories for Virtual AI Characters. - Fabian Landwehr; Erika Varis Doggett; Romann M. Weber (INLG, 2023)

Self-Supervised Effective Resolution Estimation with Adversarial Augmentations. - Manuel Kansy; Julian Balletshofer; Jacek Naruniec; Christopher Schroers; Graziana Mignone; Markus Gross 001; Romann M. Weber (WACV (Workshops), 2023)

The Score-Difference Flow for Implicit Generative Modeling. - Romann M. Weber (Trans. Mach. Learn. Res., 2023)

CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling. - Seyedmorteza Sadat; Jakob Buhmann; Derek Bradley; Otmar Hilliges; Romann M. Weber (ICLR, 2024)

LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models. - Seyedmorteza Sadat; Jakob Buhmann; Derek Bradley; Otmar Hilliges; Romann M. Weber (NeurIPS, 2024)

Reenact Anything: Semantic Video Motion Transfer Using Motion-Textual Inversion. - Manuel Kansy; Jacek Naruniec; Christopher Schroers; Markus Gross 001; Romann M. Weber (CoRR, 2024)

Eliminating Oversaturation and Artifacts of High Guidance Scales in Diffusion Models. - Seyedmorteza Sadat; Otmar Hilliges; Romann M. Weber (ICLR, 2025)

No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion Models. - Seyedmorteza Sadat; Manuel Kansy; Otmar Hilliges; Romann M. Weber (ICLR, 2025)

Guidance in the Frequency Domain Enables High-Fidelity Sampling at Low CFG Scales. - Seyedmorteza Sadat; Tobias Vontobel; Farnood Salehi; Romann M. Weber (CoRR, 2025)

HiWave: Training-Free High-Resolution Image Generation via Wavelet-Based Diffusion Sampling. - Tobias Vontobel; Seyedmorteza Sadat; Farnood Salehi; Romann M. Weber (CoRR, 2025)