CVPR 2018 LSART:《Learning Spatial-Aware Regressions for Visual Tracking》论文笔记
理解出错之处望不吝指正。 本文模型叫做LSART。本模型主要分为两条线：（1）.Spatial-Aware KRR；（2）.Spatial-Aware CNN。 Spatial-Aware KRR：KRR with Cross-Patch Similarity（KRRCPS） 传统的岭回归： 根据representer theorem（表示定理），这个优化问题可以写
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相关文章
- 1. 【小白笔记】目标跟踪LSART(learning spatial-aware regressions for visual tracking)
- 2. CVPR 2018 STRCF:《Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking》论文笔记
- 3. CVPR 2018 VITAL:《VITAL: VIsual Tracking via Adversarial Learning》论文笔记
- 4. CVPR 2018 RASNet:《Learning Attentions: Residual Attentional Siamese Network for Tracking》论文笔记
- 5. CVPR 2018 MCCT:《Multi-Cue Correlation Filters for Roubust Visual Tracking》论文笔记
- 6. Learning Spatial-Aware Regressions for Visual Tracking 阅读笔记
- 7. CVPR 2018 SINT++:《SINT++: Robust Visual Tracking via Adversarial Hard Positive Generation》论文笔记
- 8. VITAL: VIsual Tracking via Adversarial Learning论文笔记
- 9. CVPR 2017 ADNet:《 Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning》论文笔记
- 10. CVPR 2017 SANet:《SANet: Structure-Aware Network for Visual Tracking》论文笔记