This tutorial aims to explore the concepts of disentanglement and compositionality in the field of computer vision. These concepts play a crucial role in enabling machines to understand and interpret visual information with more sophistication and human-like reasoning. Participants will learn about advanced techniques and models that allow for the disentanglement of visual factors in images and the compositionality of these factors to produce more meaningful representations. All in all, Disentanglement and Composition are believed to be one of the possible ways for AI to fundamentally understand the world, and eventually achieve Artificial General Intelligence (AGI).

Please contact Xin Jin for general inquiries.