Diffusion Models and Flows

The banner image was generated via one of powerful diffusion models, FLUX, with prompt: dynamics flows of fluid

Democratizing Diffusion Models 

 This tutorial will cover the theory and practice of diffusion models for general modalities, distinguishing and comparing the modern approach such as flow-based methods. We will explain the methodology, explore its history, and demonstrate audio-visual applications such as real-time generation and various other downstream tasks. By bridging the gap from computer vision techniques and models, we aim to spark further research interest and democratize access to diffusion models for general domains. 

The tutorial comprises four sections. 

• The first provides an overview of deep generative models and delves into the fundamentals of diffusion models. 

• The second section explores applications such as utilizing pre-trained models for data editing and restoration. 

• In the third section, a hands-on demonstration will focus on audio-visual diffusion model.

• The final section outlines future research directions.

We anticipate that this tutorial, emphasizing both the foundational principles and practical implementation of diffusion models, will stimulate interest of different data modalities. It aims to illuminate insights and applications concerning diffusion models, drawn from methodologies in computer vision.

Please refer to the ICASSP tutorial page:  Accepted Tutorials – 2025 IEEE International Conference on Acoustics, Speech, and Signal Processing. 

 🎹 Please freely contact to Chieh-Hsin (Jesse) Lai via [chieh-hsin.lai@sony.com] for any question or concern.