ICCV 2017 UCT:《UCT: Learning Unified Convolutional Networks forReal-time Visual Tracking》论文笔记
理解出错之处望不吝指正。 本文模型叫做UCT。就像论文题目一样，作者提出了一个基于卷积神经网络的end2end的tracking模型。模型的整体结构如下图所示（图中实线代表online tracking过程，虚线框内和虚线表示离线训练过程和在第一帧进行训练）： 模型的目的是从样本中学习出一系列convolution filter ，则在样本上进行卷积得到的卷积response为
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相关文章
- 1. ICCV 2017 CREST：《CREST: Convolutional Residual Learning for Visual Tracking》论文笔记
- 2. ICCV 2017 DSiam:《Learning Dynamic Siamese Network for Visual Object Tracking》论文笔记
- 3. Learning Multi-Domain Convolutional Neural Networks for Visual Tracking 论文笔记
- 4. ICCV 2017 EAST:《Learning Policies for Adaptive Tracking with Deep Feature Cascades》论文笔记
- 5. 论文阅读：MDNet: Learning Multi-Domain Convolutional Neural Networks for Visual Tracking
- 6. CREST: Convolutional Residual Learning for Visual Tracking
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- 10. Learning Multi-Domain Convolutional Neural Networks for Visual Tracking CVPR 2016 阅读笔记