论文标题
利用特定场景特定功能用于对象目标导航
Exploiting Scene-specific Features for Object Goal Navigation
论文作者
论文摘要
对象与通常位于视觉导航任务中有帮助代理的房间之间的固有关系吗？我们在对象导航的背景下研究了这个问题，在这个问题中，代理在复杂的家庭环境中移动时必须到达特定类的对象。在本文中，我们介绍了一个新的减少数据集，该数据集加快了导航模型的培训，这是一项众所周知的复杂任务。我们提出的数据集允许对在合理时期不利用在线地图的模型进行培训，即使没有大量的计算资源。因此，此减少的数据集保证了大量的基准标准，并且可以用来识别有希望的模型，然后可以在更大，更具挑战性的数据集中尝试这些模型。随后，我们提出了SMTSC模型，SMTSC模型是一个基于注意力的模型，能够利用其中包含的场景和对象之间的相关性，从而定量地强调了想法的正确性。
Can the intrinsic relation between an object and the room in which it is usually located help agents in the Visual Navigation Task? We study this question in the context of Object Navigation, a problem in which an agent has to reach an object of a specific class while moving in a complex domestic environment. In this paper, we introduce a new reduced dataset that speeds up the training of navigation models, a notoriously complex task. Our proposed dataset permits the training of models that do not exploit online-built maps in reasonable times even without the use of huge computational resources. Therefore, this reduced dataset guarantees a significant benchmark and it can be used to identify promising models that could be then tried on bigger and more challenging datasets. Subsequently, we propose the SMTSC model, an attention-based model capable of exploiting the correlation between scenes and objects contained in them, highlighting quantitatively how the idea is correct.
