Object-Attribute Binding in Text-to-Image Generation: Evaluation and Control

no code implementations • 21 Apr 2024 • Maria Mihaela Trusca, Wolf Nuyts, Jonathan Thomm, Robert Honig, Thomas Hofmann, Tinne Tuytelaars, Marie-Francine Moens

Current diffusion models create photorealistic images given a text prompt as input but struggle to correctly bind attributes mentioned in the text to the right objects in the image.

Attribute Sentence +1

Limits of Transformer Language Models on Learning Algorithmic Compositions

no code implementations • 8 Feb 2024 • Jonathan Thomm, Aleksandar Terzic, Geethan Karunaratne, Giacomo Camposampiero, Bernhard Schölkopf, Abbas Rahimi

We analyze the capabilities of Transformer language models on learning discrete algorithms.

FABRIC: Personalizing Diffusion Models with Iterative Feedback

1 code implementation • 19 Jul 2023 • Dimitri von Rütte, Elisabetta Fedele, Jonathan Thomm, Lukas Wolf

In an era where visual content generation is increasingly driven by machine learning, the integration of human feedback into generative models presents significant opportunities for enhancing user experience and output quality.