Humans live in a 3D world, continually acquiring diverse skills and engaging in various activities through perceiving, understanding, and interacting with it. Our long-term research objective is centered on simulating the 3D world and empowering AI systems with 3D spatial understanding capabilities. In this talk, I will start by discussing our recent research efforts in creating 3D interactive environments by reconstruction, decomposition, and generation. Subsequently, I will explore how we can equip machines with the ability to comprehend and reason within a 3D environment by adopting a data-centric approach. Lastly, I will examine the possibilities of integrating 3D environment simulation and understanding to facilitate the emergence of closed-loop active intelligence. In summary, this talk will encompass our latest efforts in 3D reconstruction, comprehension, and creation, ultimately aiming for AI systems that can effectively navigate and engage with our 3D world.
Professor Xiaojuan Qi (https://xjqi.github.io) is an assistant professor in the Department of Electrical and Electronic Engineering at the University of Hong Kong. She received her Ph.D. from the Chinese University of Hong Kong and has worked and exchanged at the University of Toronto, Oxford University and Intel Visual Computing Group. She is committed to empowering machines with the ability to perceive, understand and reconstruct the visual world in the open world and pushing their deployments in embodied agents. She has published more than 60 papers in top computer vision and machine learning conferences such as CVPR, ICCV, NeurIPS, etc., many of which have been invited to give oral presentations. She has served/ will serve as area chair for ICCV 2021, CVPR 2021, AAAI 2021, AAAI 2022, CVPR 2023, NeurIPS 2023, and CVPR 2024.
Clean water and clean air are vital for public health. This project focuses on developing high-efficiency and environmentally sustainable filters for removing harmful air/water pollutants. The team has developed novel architectures and functionalities for the filters to achieve high permeance, high removal efficiency, and excellent reusability.
