3 accepted papers
Fine-grained 3D shape classification (FGSC) remains challenging due to the difficulty of adaptively capturing global structure differences and subtle inter-class distinctions. This paper directly extends Vision Transformer (ViT) to FGSC, proposing a pure Transformer network FG3DFormer that fully lev…
The emergence of non-fingered soft bioinspired grippers poses a challenge for learning-based grasping control due to the lack of a model describing grasping robustness and a dataset for training. In this letter, we propose a comprehensive pipeline encompassing grasping evaluation, dataset generation
Long-term scene changes pose challenges to localization systems using a pre-built map. This paper presents a LiDAR-based system that provides robust localization against those challenges. Our method starts with activation of a mapping process temporarily when global matching towards the pre-built ma…