  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, colour, and severe
occlusion provide a significant real world challenge for the computer vision
community. An accompanying ground-truthing tool for superpixel labeling, Truth
and Crop, is also introduced. Finally, we provide a baseline using a variant of
Fully Convolutional Networks, and report results in terms of the standard mean
intersection over union (mIoU) metric.
