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
Discovery Early Career Researcher Award - Grant ID: DE230101058
Funder
Australian Research Council
Funding Amount
$437,254.00
Summary
Glass-box Deep Machine Perception for Trustworthy Artificial Intelligence. Explainability and Transparency are the key values for development and deployment of Artificial Intelligence (AI) in Australia’s AI Ethics Framework for industry and governments. This project aims to build new tools to make the central technology of AI - deep learning - transparent and explainable. Its expected outputs are novel theory-driven algorithms and unconventional foundational blocks for deep learning that will al ....Glass-box Deep Machine Perception for Trustworthy Artificial Intelligence. Explainability and Transparency are the key values for development and deployment of Artificial Intelligence (AI) in Australia’s AI Ethics Framework for industry and governments. This project aims to build new tools to make the central technology of AI - deep learning - transparent and explainable. Its expected outputs are novel theory-driven algorithms and unconventional foundational blocks for deep learning that will allow humans to clearly interpret the reasoning process of this technology, which is currently not possible. It is expected to significantly advance our knowledge in machine intelligence and perception. Due to their fundamental nature, the project outcomes are likely to benefit industry and scientific frontiers alike.Read moreRead less
ARC Centre of Excellence for Engineered Quantum Systems. This Centre aims to build sophisticated quantum machines to harness the quantum world for the future health, economy, environment and security of Australian society. It intends to pioneer the designer quantum materials, engines and imaging systems at the heart of these machines. It also solves the most challenging research problems at the interface of basic quantum physics and engineering. The Centre will work with industry partners to tra ....ARC Centre of Excellence for Engineered Quantum Systems. This Centre aims to build sophisticated quantum machines to harness the quantum world for the future health, economy, environment and security of Australian society. It intends to pioneer the designer quantum materials, engines and imaging systems at the heart of these machines. It also solves the most challenging research problems at the interface of basic quantum physics and engineering. The Centre will work with industry partners to translate these research discoveries into practical applications and devices. It will train scientists in research, innovation, and entrepreneurship, which is expected to affect Australia’s high-tech economy.Read moreRead less
A Machine Learning Framework for Concrete Workability Estimation . Concrete is the most used construction material in Australia. The project aims to develop a system to measure the workability of concrete in transit in agitator trucks using advanced machine vision and machine learning, and provide a reliable alternative to the current practice of visually testing concrete workability by certified testers. Concrete that fails to meet workability requirements is one of the most frequent reasons fo ....A Machine Learning Framework for Concrete Workability Estimation . Concrete is the most used construction material in Australia. The project aims to develop a system to measure the workability of concrete in transit in agitator trucks using advanced machine vision and machine learning, and provide a reliable alternative to the current practice of visually testing concrete workability by certified testers. Concrete that fails to meet workability requirements is one of the most frequent reasons for rejection at construction sites, resulting in significant costs, waste, and delays. Multimodal data sources will be used to provide a reliable workability estimate in real time, enabling construction teams to identify and rectify workability issues in transit while continuously monitoring the adjustments effects.Read moreRead less
Real-time global optimisation for distributed parameter control systems. This project aims to develop real-time optimal control algorithms for distributed parameter systems involving both time and spatial variables and multiple time-delays, with a focus on mining and energy applications. Current optimal control algorithms for such systems are too slow for real-time use and often get trapped at local optima, which can be vastly inferior to the global solution. This project will result in a new op ....Real-time global optimisation for distributed parameter control systems. This project aims to develop real-time optimal control algorithms for distributed parameter systems involving both time and spatial variables and multiple time-delays, with a focus on mining and energy applications. Current optimal control algorithms for such systems are too slow for real-time use and often get trapped at local optima, which can be vastly inferior to the global solution. This project will result in a new optimal control framework, underpinned by recent advances in constraint propagation, switching surface optimisation, and input regularisation. It will result in cutting-edge mathematical tools to complement and exploit new technologies and optimise key processes in natural gas liquefaction and zinc and alumina production, increasing efficiency and reducing the ecological footprint. This project will lead to new cutting-edge control algorithms for replacing the inefficient manual operations endemic in Australia’s natural gas and mineral processing plants.Read moreRead less
Personalised Privacy-Preserving Network Data Publishing System . Data sharing has become a driving force for many businesses in industrial sectors. This project aims to develop a privacy preserving network data publishing system that can preserve user privacy in a personalised way while maintaining maximal utility of the published data. To make accurate privacy preservation, this project will design novel learning models to derive accurate users’ correlation and their privacy intention, develop ....Personalised Privacy-Preserving Network Data Publishing System . Data sharing has become a driving force for many businesses in industrial sectors. This project aims to develop a privacy preserving network data publishing system that can preserve user privacy in a personalised way while maintaining maximal utility of the published data. To make accurate privacy preservation, this project will design novel learning models to derive accurate users’ correlation and their privacy intention, develop efficient privacy preserving algorithms to deal with static and dynamic network data sharing. The success of this project will benefit many industries and government agencies to reduce users’ privacy breaches, avoid illegal consequences of sharing data, and enhance these service providers’ service quality.Read moreRead less