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arXiv · 1702.05564

The Ciona17 Dataset for Semantic Segmentation of Invasive Species in a Marine Aquaculture Environment

Angus Galloway·Graham W. Taylor·Aaron Ramsay·Medhat Moussa
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Abstract

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.

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Angus Galloway, Graham W. Taylor, Aaron Ramsay, Medhat Moussa. 2017-02-18. The Ciona17 Dataset for Semantic Segmentation of Invasive Species in a Marine Aquaculture Environment. https://doi.org/10.5683/sp/ntuok9

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