6D Pose Estimation

6D pose estimation aims to determine the three-dimensional position and orientation of objects in a scene, a crucial task for robotics and augmented reality. Current research emphasizes improving accuracy and robustness, particularly for challenging scenarios like occlusion, symmetry, and textureless objects, often employing deep learning architectures such as transformers and convolutional neural networks, along with techniques like render-and-compare and multi-view fusion. These advancements are driving progress in applications ranging from robotic manipulation and grasping to autonomous navigation and industrial automation, where reliable object pose understanding is essential for safe and efficient operation.