This repo contains a TensorFlow implementation of weakly supervised instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017). The idea behind weakly supervised segmentation is to train a model using cheap-to-generate label approximations (e.g., bounding boxes) as substitute/guiding labels for computer vision classification tasks that usually require very detailed labels. In semantic labelling, each image pixel is assigned to a specific class (e.g., boat, car, background, etc.). In instance segmentation, all the pixels belonging to the same object instance are given the same instance ID.