Text-conditioned image editing has recently attracted considerable interest. However, most
methods are currently limited to one of the following: specific editing types (eg, object …

Diffusion probabilistic models (DPMs) have achieved impressive success in high-resolution
image synthesis, especially in recent large-scale text-to-image generation applications. An …

Deep generative models have unlocked another profound realm of human creativity. By
capturing and generalizing patterns within data, we have entered the epoch of all …

Guided sampling is a vital approach for applying diffusion models in real-world tasks that
embeds human-defined guidance during the sampling procedure. This paper considers a …

Text-to-image diffusion models often make implicit assumptions about the world when
generating images. While some assumptions are useful (eg, the sky is blue), they can also …

By optimizing the rate-distortion-realism trade-off, generative compression approaches
produce detailed, realistic images, even at low bit rates, instead of the blurry reconstructions …

This paper outlines an end-to-end optimized lossy image compression framework using
diffusion generative models. The approach relies on the transform coding paradigm, where …

Image Inpainting is an age-old image processing problem, with people from different eras
attempting to solve it using various methods. Traditional image inpainting algorithms have …

Recently, Rissanen et al.,(2022) have presented a new type of diffusion process for
generative modeling based on heat dissipation, or blurring, as an alternative to isotropic …

The emerging conditional coding-based neural video codec (NVC) shows superiority over
commonly-used residual coding-based codec and the latest NVC already claims to …