Diffusion models have recently gained unprecedented attention in the field of image
synthesis due to their remarkable generative capabilities. Notwithstanding their prowess …

The field of image synthesis is currently flourishing due to the advancements in diffusion
models. While diffusion models have been successful their computational intensity has …

One of the key components within diffusion models is the UNet for noise prediction. While
several works have explored basic properties of the UNet decoder, its encoder largely …

Multi-modal generative AI has received increasing attention in both academia and industry.
Particularly, two dominant families of techniques are: i) The multi-modal large language …

Diffusion probabilistic models (DPMs) have shown remarkable performance in high-
resolution image synthesis but their sampling efficiency is still to be desired due to the …

Diffusion models have become a mainstream approach for high-resolution image synthesis.
However, directly generating higher-resolution images from pretrained diffusion models will …

Diffusion models (DMs) have exhibited superior performance in generating high-quality and
diverse images. However this exceptional performance comes at the cost of expensive …

Flow matching is a powerful framework for generating high-quality samples in various
applications, especially image synthesis. However, the intensive computational demands of …

As recent advances in large-scale Text-to-Image (T2I) diffusion models have yielded
remarkable high-quality image generation, diverse downstream Image-to-Image (I2I) …

Diffusion models have revolutionized text-to-image generation, but their real-world
applications are hampered by the extensive time needed for hundreds of diffusion steps …