Adding New Classes in Semantic Segmentation

To implement semantic segmentation and assign one of the classes to each pixel, a large amount of pixel labelled images are required. However, annotations in existing image datasets are limited both in terms of quantity and diversity owing to the heavy annotation cost. Therefore, in this study, we examined a method to readily add new classes of training images and evaluate feasibility by testing semantic segmentation on car-mounted camera images.