Object Model

Object models are computational representations of objects, aiming to capture their visual and physical properties for various applications like robotics and computer vision. Current research focuses on improving object detection and pose estimation, particularly for challenging scenarios involving oriented, textureless, or articulated objects, often employing deep learning architectures like GANs and autoencoders, along with novel algorithms for handling symmetries and occlusions. These advancements are crucial for enabling robots to interact with the world more effectively and for improving the accuracy and efficiency of computer vision systems in diverse real-world settings.