We develop a RGB-D scene recognition model based on object-scene relation(RSBR). First learning a Semantic Network in the semantic domain that classifies the label of a scene on the basis of the labels of all object types. Then, we design an Appearance Network in the appearance domain that recognizes the scene according to local captions. We enforce the Semantic Network to guide the Appearance Network in the learning procedure. Based on the proposed RSBR model, we obtain the state-of-the-art results of RGB-D scene recognition on SUN RGB-D and NYUD2 datasets.
翻译:我们开发了一个基于天体-光谱关系(RSBR)的 RGB-D 场景识别模型。 我们首先在语义域学习了一个语义网络,根据所有对象类型的标签对场景标签进行分类。 然后, 我们设计了一个外观域的外观网络, 根据本地字幕识别场景。 我们实施语义网络, 在学习过程中指导外观网络。 根据拟议的 RSBR 模型, 我们在 SUN RGB-D 和 NYUD2 数据集中获取 RGB-D 场景识别的最新结果 。