Indoor RGB-D semantic segmentation is a new and chal- lenging problem. Traditional methods usually apply two- stream convolutional neural networks (CNNs) to represent RGB and depth images respectively, and fuse the two streams on a specific layer. In this paper, we explore several fusion strategies