BriefGPT.xyz
Aug, 2019
利用时间性进行半监督视频分割
Exploiting Temporality for Semi-Supervised Video Segmentation
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Radu Sibechi, Olaf Booij, Nora Baka, Peter Bloem
TL;DR
本文提出了一种端到端可训练的深度学习模型,利用时间信息来利用易于获取的未标记数据,从而解决了视频分割中标签稀缺的问题。实验结果表明,该模型能够显著优于基线方法和逐帧图像分割。
Abstract
In recent years, there has been remarkable progress in supervised image segmentation.
video segmentation
is less explored, despite the temporal dimension being highly informative.
semantic labels
, e.g. that canno
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