103 citations · 129 across the 11 of their papers we have counts for
4 papers · 1 filter
MONET: A Massive, Open, Non-redundant and Enriched Text-to-image dataset
Benjamin Aubin, Gonzalo Iñaki Quintana, Onur Tasar +4
Training large text-to-image models requires high-quality, curated datasets with diverse content and detailed captions. Yet the cost and complexity of collecting, filtering, dedupl…
LBM: Latent Bridge Matching for Fast Image-to-Image Translation
Clément Chadebec, Onur Tasar, Sanjeev Sreetharan +1
In this paper, we introduce Latent Bridge Matching (LBM), a new, versatile and scalable method that relies on Bridge Matching in a latent space to achieve fast image-to-image trans…
Controllable Shadow Generation with Single-Step Diffusion Models from Synthetic Data
Onur Tasar, Clément Chadebec, Benjamin Aubin
Realistic shadow generation is a critical component for high-quality image compositing and visual effects, yet existing methods suffer from certain limitations: Physics-based appro…
Flash Diffusion: Accelerating Any Conditional Diffusion Model for Few Steps Image Generation
Clément Chadebec, Onur Tasar, Eyal Benaroche +1
In this paper, we propose an efficient, fast, and versatile distillation method to accelerate the generation of pre-trained diffusion models: Flash Diffusion. The method reaches st…