ICCV 2017 DSiam:《Learning Dynamic Siamese Network for Visual Object Tracking》论文笔记

时间 2020-12-23

标签目标跟踪 ICCV2017 DSiam 栏目系统网络繁體版

原文原文链接

理解出错之处望不吝指正。本文模型叫做DSiam。作者提出一个Dynamic Siamese Network，可以使用一个transformation learning model来在线学习目标的外观变化并且压制背景信息。本文的另一个创新点在于作者提出了一个自适应聚合各个层的特征的方法（elementwise multi-layer fusion）。并且，本模型不用像以往的基于Siames

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1. DSiam阅读笔记：Learning Dynamic Siamese Network for Visual Object Tracking
2. Learning Dynamic Siamese Network for Visual Object Tracking—ICCV2017 阅读
3. ICCV 2017 CREST：《CREST: Convolutional Residual Learning for Visual Tracking》论文笔记
4. 论文笔记：Learning Dynamic Memory Networks for Object Tracking
5. ICCV 2017 EAST:《Learning Policies for Adaptive Tracking with Deep Feature Cascades》论文笔记
6. ECCV 2018 《Triplet Loss in Siamese Network for Object Tracking》论文笔记
7. Siamese Attentional Keypoint Network for High Performance Visual Tracking--论文笔记
8. ICCV 2017 UCT:《UCT: Learning Unified Convolutional Networks forReal-time Visual Tracking》论文笔记
9. 《Siamese RPN：High Performance Visual Tracking with Siamese Region Proposal Network》论文笔记
10. CVPR 2018 RASNet:《Learning Attentions: Residual Attentional Siamese Network for Tracking》论文笔记
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1. DSiam阅读笔记：Learning Dynamic Siamese Network for Visual Object Tracking
2. Learning Dynamic Siamese Network for Visual Object Tracking—ICCV2017 阅读
3. ICCV 2017 CREST：《CREST: Convolutional Residual Learning for Visual Tracking》论文笔记
4. 论文笔记：Learning Dynamic Memory Networks for Object Tracking
5. ICCV 2017 EAST:《Learning Policies for Adaptive Tracking with Deep Feature Cascades》论文笔记
6. ECCV 2018 《Triplet Loss in Siamese Network for Object Tracking》论文笔记
7. Siamese Attentional Keypoint Network for High Performance Visual Tracking--论文笔记
8. ICCV 2017 UCT:《UCT: Learning Unified Convolutional Networks forReal-time Visual Tracking》论文笔记
9. 《Siamese RPN：High Performance Visual Tracking with Siamese Region Proposal Network》论文笔记
10. CVPR 2018 RASNet:《Learning Attentions: Residual Attentional Siamese Network for Tracking》论文笔记

>>更多相关文章<<