Text to Scene
Xinyan Yang, Fei Hu, Long Ye · 2021
In this work, we show the Text to Scene system, which can configure 3D indoor scene from natural language. Given a text, the system will organize inclusive semantic message to a graph template, complete the graph with a novel graph-based contextual completion method Contextual ConvE(CConvE) and visulize the graph by arranging 3D models under an object location protocol. In the experiments, qualitative results obtained by the Text to Scene(T2S) system and quantitative evaluation of CConvE compared with other state-of-the-art approaches are reported.