Multi-class indoor semantic segmentation with deep structured model

Indoor semantic segmentation plays a critical role in many applications, such as intelligent robots. However, multi-class recognition is still challenging, especially for pixel-level indoor semantic labeling. In this paper, a novel deep structured …

Learning aggregated features and optimizing model for semantic labeling

Semantic labeling for indoor scenes has been extensively developed with the wide availability of affordable RGB-D sensors. However, it is still a challenging task for multi-class recognition, especially for “small” objects. In this paper, a novel …

Learning contextual information for indoor semantic segmentation"