2024
Joint-Loss Enhanced Self-Supervised Learning for Refinement-Coupled Object 6D Pose Estimation
ICRA 2024poster
6D object pose estimation plays a crucial role in robot grasping and manipulation. However, the prevalent methods for 6D object pose estimation heavily rely on 6D annotated data to train deep neural networks, which poses challenges due to the difficulty in obtaining sufficient pose annotations. To a…