Towards Human-like Machine Perception for Embodied AI

该项目旨在研究类似人类的视觉感知，借此人工智能机器可以像人类一样看到和解释世界。预期的输出将使人工智能机器能够通过一套深度学习技术进行以人为中心的视觉识别和注释高效学习，并能够通过强化学习方法主动收集视觉信息(用于决策支持)。这项研究是创造具体化人工智能机器的基础，预计它将在工业、教育和医疗方面为人类提供帮助。因此，它将表明立即应用于自动驾驶汽车和家用机器人，为澳大利亚提供科学、社会和经济利益。

This project aims to investigate human-like visual perception, whereby AI machines can see and interpret the world like a human. The expected outputs will empower AI machines with the abilities of human-centered visual recognition and annotation-efficient learning through a set of deep learning techniques, and the ability to actively gather visual information through a reinforcement learning methodology (for decision support). This research is fundamental to the creation of embodied AI machines, which are expected to provide assistance to humans in industry, education and health. It thus will indicate immediate applications embracing autonomous vehicles and domestic robotics, providing scientific, social and economic benefits for Australia.