DASiamRPN阅读笔记：Distractor-aware Siamese Networks for Visual Object Tracking
发表在ECCV2018上 作者的知乎讲解：https://zhuanlan.zhihu.com/p/42546692 三个问题： 1.常见的siam类跟踪方法只能区分目标和无语义信息的背景，当有语义的物体是背景时，也就是有干扰物（distractor）时，表现不是很好。 2.大部分siam类跟踪器在跟踪阶段不能更新模型，训练好的模型对不同特定目标都是一样的。这样带来了高速度，也相应牺牲了精度。 3
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相关文章
- 1. Distractor-aware Siamese Networks for Visual Object Tracking（DaSiamRPN)
- 2. ECCV 2018 DaSiamRPN:《Distractor-aware Siamese Networks for Visual Object Tracking》论文笔记
- 3. DSiam阅读笔记：Learning Dynamic Siamese Network for Visual Object Tracking
- 4. C-RPN阅读笔记：Siamese Cascaded Region Proposal Networks for Real-Time Visual Tracking
- 5. SiamDW阅读笔记：Deeper and Wider Siamese Networks for Real-Time Visual Tracking
- 6. SiamFC:Fully-Convolutional Siamese Networks for Object Tracking
- 7. Fully-Convolutional Siamese Networks for Object Tracking
- 8. 论文笔记Deformable Siamese Attention Networks for Visual Object Tracking
- 9. 目标跟踪论文（三）：DaSiamRPN：Distractor-Aware Siamese Networks for Visual Object Tracking
- 10. Learning Dynamic Siamese Network for Visual Object Tracking—ICCV2017 阅读