تقرير
Answerability Fields: Answerable Location Estimation via Diffusion Models
| العنوان: | Answerability Fields: Answerable Location Estimation via Diffusion Models |
|---|---|
| المؤلفون: | Azuma, Daichi, Miyanishi, Taiki, Kurita, Shuhei, Sakamoto, Koya, Kawanabe, Motoaki |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition |
| الوصف: | In an era characterized by advancements in artificial intelligence and robotics, enabling machines to interact with and understand their environment is a critical research endeavor. In this paper, we propose Answerability Fields, a novel approach to predicting answerability within complex indoor environments. Leveraging a 3D question answering dataset, we construct a comprehensive Answerability Fields dataset, encompassing diverse scenes and questions from ScanNet. Using a diffusion model, we successfully infer and evaluate these Answerability Fields, demonstrating the importance of objects and their locations in answering questions within a scene. Our results showcase the efficacy of Answerability Fields in guiding scene-understanding tasks, laying the foundation for their application in enhancing interactions between intelligent agents and their environments. Comment: IROS2024 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2407.18497 |
| رقم الأكسشن: | edsarx.2407.18497 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |