3. 数据集是DAVIS(79.8%)和Youtube-Object(68.0%) CVPR 2017,原文链接:http://arxiv.org/abs/1611.05198 原文开源代码:http://www.vision.ee.ethz.ch/~cvlsegmentation/osvos/ 本文作于2020年5月14日。 1、摘要 This paper tackles the task ofsemi-supervised video object segmentation, i.e., the sepa...
3.One-Shot 深度学习 我们训练了用于分离前景和背景的二元FCN,接着又在包含物体的大量数据上训练通用前景物体识别模型(“It is this particular object.” ),最后在一个小的特定实例上finetune以分割出特定物体(“It is this particular object.” )。 3.1. 端到端可训练前景FCN 4.实验验证 5.结论 使用深度学...
论文笔记STM:Video Object Segmentation using Space-Time Memory Networks STM首次将Memory Network引入VOS领域,引申为一个space-tine的memory network,并实现了较好的分割准确率以及较快的速度。DAVIS2020大赛很多优秀的模型都是根据STM进行改造的,可见其具有很棒的指导意义和研究价值。在STM出现之间,VOS的方法基本包括以...
OSVOS: One-Shot Video Object Segmentation Check our project page for additional information. OSVOS is a method that tackles the task of semi-supervised video object segmentation. It is based on a fully-convolutional neural network architecture that is able to successively transfer generic semantic ...
This is the implementation of our workOne-Shot Video Object Segmentation (OSVOS), for semi-supervised video object segmentation. OSVOS is based on a fully convolutional neural network architecture that is able to successively transfer generic semantic information, learned on ImageNet, to the task of...
This branch is14 commits behindscaelles/OSVOS-TensorFlow:master. README OSVOS: One-Shot Video Object Segmentation Check ourproject pagefor additional information. OSVOS is a method that tackles the task of semi-supervised video object segmentation. It is based on a fully-convolutional neural network...