The Ciona17 dataset for semantic segmentation of invasive species in a marine aquaculture environment

An original dataset for semantic segmentation, Ciona17, is introduced, which to the best of the authors' knowledge, is the first dataset of its kind with pixel-level annotations pertaining to invasive species in a marine environment. Diverse outdoor illumination, a range of object shapes, and severe occlusion provide a significant challenge for the computer vision community. An accompanying ground-truthing tool for superpixel labeling, Truth and Crop, is also introduced. In a subsequent work, results are reported in terms of the mean intersection over union (mIoU) with segmentation mask. The GUI application for ground-truthing semantic segmentation datasets in PyQt4/OpenCV can be accessed at https://github.com/AngusG/truth-and-crop