تقرير
Open-Vocabulary Affordance Detection using Knowledge Distillation and Text-Point Correlation
| العنوان: | Open-Vocabulary Affordance Detection using Knowledge Distillation and Text-Point Correlation |
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| المؤلفون: | Van Vo, Tuan, Vu, Minh Nhat, Huang, Baoru, Nguyen, Toan, Le, Ngan, Vo, Thieu, Nguyen, Anh |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Robotics |
| الوصف: | Affordance detection presents intricate challenges and has a wide range of robotic applications. Previous works have faced limitations such as the complexities of 3D object shapes, the wide range of potential affordances on real-world objects, and the lack of open-vocabulary support for affordance understanding. In this paper, we introduce a new open-vocabulary affordance detection method in 3D point clouds, leveraging knowledge distillation and text-point correlation. Our approach employs pre-trained 3D models through knowledge distillation to enhance feature extraction and semantic understanding in 3D point clouds. We further introduce a new text-point correlation method to learn the semantic links between point cloud features and open-vocabulary labels. The intensive experiments show that our approach outperforms previous works and adapts to new affordance labels and unseen objects. Notably, our method achieves the improvement of 7.96% mIOU score compared to the baselines. Furthermore, it offers real-time inference which is well-suitable for robotic manipulation applications. Comment: 8 pages |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2309.10932 |
| رقم الأكسشن: | edsarx.2309.10932 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |