Learning Multi-Domain Convolutional Neural Networks for Visual Tracking
tracking任务的一篇经典文章，2015年VOT的冠军，首次将深度学习引入tracking任务，并超越了当时的所有人工算法。 论文地址：https://arxiv.org/abs/1510.07945v1 代码地址：https://github.com/HyeonseobNam/MDNet 1.背景 对于tracking任务而言，存在着诸多问题，主要集中在以尺度、光照、遮挡、形变、模糊等方面的
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相关文章
- 1. MDNet: Learning Multi-Domain Convolutional Neural Networks for Visual Tracking
- 2. ROLO:Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object Tracking
- 3. 论文阅读：MDNet: Learning Multi-Domain Convolutional Neural Networks for Visual Tracking
- 4. Learning Multi-Domain Convolutional Neural Networks for Visual Tracking CVPR 2016 阅读笔记
- 5. Learning Multi-Domain Convolutional Neural Networks for Visual Tracking 论文笔记
- 6. 深度学习笔记（一）：Learning Multi-Domain Convolutional Neural Networks for Visual Tracking
- 7. CREST: Convolutional Residual Learning for Visual Tracking
- 8. Learning Convolutional Neural Networks for Graphs
- 9. Convolutional Neural Networks for Visual Recognition
- 10. CS231n Convolutional Neural Networks for Visual Recognition