Many robotic applications rely on robotic arms or hands to handle different types of objects. Estimating the pose of such hand-held objects is an important yet challenging task in robotics, computer ...

Three-dimensional object tracking and pose estimation represent a pivotal area of research in computer vision, with applications ranging from augmented reality to autonomous navigation and robotics.

Recent work in 6D object pose estimation holds significant promise for advancing robotics, augmented reality (AR), virtual reality (VR), as well as autonomous navigation. The research, published in ...

Researchers have developed a novel 6D pose dataset designed to improve robotic grasping accuracy and adaptability in industrial settings. The dataset, which integrates RGB and depth images, ...

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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 ...