PASCAL-Context dataset augments PASCAL VOC 2010 dataset with annotations for 400+ additional categories. The dataset contains semantic segmentation annotations for 10,103 images in the Training and Validation subsets of PASCAL VOC 2010 dataset. The previous annotations covered around 29% of pixels in the dataset, while ours covers 100% of pixels. The dataset contains annotations for things (e.g., keyboard, fork), stuff (e.g., sky, water) and hybrids (e.g., road) that have clear boundaries, but their shape is more complex than the shape of things.Related publication:Roozbeh Mottaghi, Xianjie Chen, Xiaobai Liu, Nam-Gyu Cho, Seong-Whan Lee, Sanja Fidler, Raquel Urtasun, Alan Yuille "The Role of Context for Object Detection and Semantic Segmentation in the Wild" IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014 [PDF]