A. Galloway, Graham W. Taylor, Aaron Ramsay, M. Moussa
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引用次数: 9
摘要
介绍了语义分割的原始数据集Ciona17,据作者所知,这是同类数据集中第一个具有与海洋环境中入侵物种相关的像素级注释的数据集。不同的室外照明,各种物体形状,颜色和严重遮挡为计算机视觉社区提供了一个重大的现实世界挑战。此外,还介绍了一种用于超像素标记的地面真实工具Truth and Crop。最后,我们使用全卷积网络的一种变体提供了一个基线,并根据标准平均交联(mIoU)度量报告了结果。
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, 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.