Openable Part

Openable part detection focuses on identifying and characterizing parts of objects that can open, along with their associated movement parameters, from images or 3D models. Current research emphasizes improving the accuracy and robustness of detection across multiple objects and complex scenes, employing techniques like transformer networks and coarse-to-fine segmentation approaches. This research is significant for advancing computer vision and robotics, enabling applications such as improved 3D modeling, interactive object manipulation in virtual and augmented reality, and more realistic scene understanding in autonomous systems. Challenges remain in handling real-world complexities and achieving generalization across diverse object categories.