Estimating the pose of hand-held objects is a critical and challenging problem in robotics and computer vision. While leveraging multi-modal RGB and depth data is a promising solution, existing ...

The proposed framework will enable robots to accurately and more efficiently handle complex objects, while also advancing augmented reality technologies to support more lifelike hand-object ...

However, existing approaches still face two main challenges. First, they face accuracy drops when hands occlude the objects held, obscuring critical features required for pose estimation. Additionally ...

A new AI-powered framework has been developed, offering new capabilities for the real-time analysis of two hands engaged in manipulating an object. A research team led by Professor Seungryul Baek from ...