3 papers
cs.CV2026
Autoguided Online Data Curation for Diffusion Model Training
Valeria Pais, Luis Oala, Daniele Faccio +1
The costs of generative model compute rekindled promises and hopes for efficient data curation. In this work, we investigate whether recently developed autoguidance and online data…
cs.LG2024
Generative Fractional Diffusion Models
Gabriel Nobis, Maximilian Springenberg, Marco Aversa +11
We introduce the first continuous-time score-based generative model that leverages fractional diffusion processes for its underlying dynamics. Although diffusion models have excell…
cs.CV2024
Is One GPU Enough? Pushing Image Generation at Higher-Resolutions with Foundation Models
Athanasios Tragakis, Marco Aversa, Chaitanya Kaul +2
In this work, we introduce Pixelsmith, a zero-shot text-to-image generative framework to sample images at higher resolutions with a single GPU. We are the first to show that it is…