Mar 30, 2023 · Abstract:We propose a simple, efficient, yet powerful framework for dense visual predictions based on the conditional diffusion pipeline.

We propose a simple, efficient, yet powerful framework for dense visual predictions based on the conditional dif- fusion pipeline.

This paper introduced DDP, a simple, efficient, yet powerful framework for dense visual predictions based on conditional diffusion. It extends the denoising ...

We propose a simple, efficient, yet powerful framework for dense visual predictions based on the conditional diffusion pipeline. Our approach follows a.

The method, called DDP, efficiently extends the denoising diffusion process into the modern perception pipeline and shows attractive properties such as ...

Feb 10, 2024 · We propose a simple, efficient, yet powerful framework for dense visual predictions based on the conditional diffusion pipeline.

We propose a simple, efficient, yet powerful framework for dense visual predictions based on the conditional diffusion pipeline.

Feb 10, 2024 · DDP [26] designs a dense prediction framework with stepwise denoising refinement guided by image features. ODISE [57] combines a trained text ...

The objective for establishing dense correspondence between paired images con- sists of two terms: a data term and a prior term.

This work highlights the efficacy of text-to-image diffusion models and believes that the embedded visual semantic knowledge (inside these models) can benefit ...