Our guest speaker is Daiqing Li from Playground.

You are all cordially invited to the CVG Seminar on December 7th at 4 pm CET

• via Zoom (passcode is 102781).

Abstract

Diffusion-based deep generative models have demonstrated remarkable performance in text condition synthesis tasks in images, videos, and 3D. In this talk, I will talk about how to use large-scale T2I models as vision foundation models for representation learning and other downstream tasks, such as synthetic dataset generation and semantic segmentation.

Bio

Daiqing Li is currently serving as a research lead at Playground, where their primary focus lies in advancing the realm of pixel foundation models. Previously, Daiqing held the position of senior research scientist at the NVIDIA Toronto AI Lab. In this capacity, their research encompassed a broad spectrum, including computer vision, computer graphics, generative models, and machine learning. He collaborates closely with Sanja Fidler and Antonio Torralba in NVIDIA and several of his works have been integrated into NVIDIA products, notably Omniverse and Clara. Daiqing graduated from the University of Toronto and has been recognized as the runner-up for the MICCAI Young Scientist Awards. His recent research focuses on using generative models for dataset synthesis, perception tasks, and representation learning. He is the author of SemanticGAN, BigDatasetGAN, and DreamTeacher.