3D Diffusion Models for Generating and Understanding 3D Scenes. Diffusion models, such as DALL-E2 and Imagen, have achieved remarkable success in generating photorealistic images and hold promise to solve long-standing computer vision problems. However, 3D scene generation remains unexplored. This research project aims to bridge the gap by developing 3D diffusion models capable of generating complete 3D scenes. This will advance our theoretical understanding of diffusion in complex 3D environmen ....3D Diffusion Models for Generating and Understanding 3D Scenes. Diffusion models, such as DALL-E2 and Imagen, have achieved remarkable success in generating photorealistic images and hold promise to solve long-standing computer vision problems. However, 3D scene generation remains unexplored. This research project aims to bridge the gap by developing 3D diffusion models capable of generating complete 3D scenes. This will advance our theoretical understanding of diffusion in complex 3D environments and open up new possibilities for applications in fields such as virtual reality, architecture, and city planning. The proposed 3D diffusion models will also enhance the accuracy of computer vision tasks related to 3D scene understanding, such as object detection, tracking, and semantic segmentation.Read moreRead less
Effective and Efficient Query Processing over Dynamic Social Networks. This project aims to invent novel query-based social network data exploration techniques which would help individuals or organisations make smart decisions based on data from increasingly massive, complex and dynamic social networks. Expected project outcomes are formal result semantics, advanced indices, efficient query evaluation algorithms and scalable techniques for three types of commonly used queries. The project plans ....Effective and Efficient Query Processing over Dynamic Social Networks. This project aims to invent novel query-based social network data exploration techniques which would help individuals or organisations make smart decisions based on data from increasingly massive, complex and dynamic social networks. Expected project outcomes are formal result semantics, advanced indices, efficient query evaluation algorithms and scalable techniques for three types of commonly used queries. The project plans to develop a system prototype to evaluate the effectiveness and efficiency of the proposed approaches and techniques. Query-based dynamic social network data exploration techniques developed in this project may have practical applications including event and influential topic discovery and tracking, buying trend analysis and political issues analysis.Read moreRead less
Efficient structure search over large graphs. The project aims to develop advanced search technology to support large-scale graph applications. The success of the project not only brings a breakthrough in technology development but also provides training for high quality personnel in this important and growing area, and brings considerable economic and social benefits to Australia.