In recent years, diffusion models have rapidly overtaken previous methods to become the dominant approach in visual generative modeling, with widespread applications in generating images, videos, 3D objects, and more. However, these models also come with notable limitations, such as slow generation speeds, limited human intervention during the generation process, and challenges in modeling complex distributions like long videos.
This year, our Visual Generative Modeling workshop at CVPR aims to explore what lies beyond diffusion models in visual generative modeling. We will discuss novel insights, alternative approaches, and new possibilities in modeling and generating visual data. Join us for a full-day event featuring keynote talks from top universities and industrial labs -- all designed to ignite innovative ideas and novel research in visual generative modeling.
Detailed schedules will be updated later.
