CVPR18读文笔记：SINT++：Robust Visual Tracking via Adversarial Postive Instance Generation

时间 2021-01-02

标签 CVPR2018 tracking VAE deep reinforcement learning SINT 繁體版

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CVPR18一共出现了3篇将Adersarial概念应用于tracking，解决正样本弱的问题。VITAL是用了GAN，惊为天人。本文国产，索然性能不是最优，但是VAE+DRL+SINT的集大成之作，还是足够significant。本文主旨： Improve the robustness of visual tracking through the generation of hard posi

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1. VITAL: Visual Tracking via Adversarial Learning 阅读笔记
2. CVPR 2018 SINT++:《SINT++: Robust Visual Tracking via Adversarial Hard Positive Generation》论文笔记
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4. CVPR2018读文笔记：VITAL：VIsual Tracking via Adversarial Learning
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1. VITAL: Visual Tracking via Adversarial Learning 阅读笔记
2. CVPR 2018 SINT++:《SINT++: Robust Visual Tracking via Adversarial Hard Positive Generation》论文笔记
3. VITAL: VIsual Tracking via Adversarial Learning论文笔记
4. CVPR2018读文笔记：VITAL：VIsual Tracking via Adversarial Learning
5. CVPR 2018 VITAL:《VITAL: VIsual Tracking via Adversarial Learning》论文笔记
6. 【小白笔记】目标跟踪VIVAT(Visual Tracking via Adversarial Learning)论文笔记
7. Automatic generation of sentimental texts via mixture adversarial networks读书笔记
8. 《Long Text Generation via Adversarial Training with Leaked Information》阅读笔记
9. 论文笔记之《Cell Tracking via Proposal Generation and Selection》
10. AAAI2018-Long Text Generation via Adversarial Training with Leaked Information论文笔记

>>更多相关文章<<