論文閱讀：MDNet: Learning Multi-Domain Convolutional Neural Networks for Visual Tracking
CVPR2016 來自Korea的POSTECH這個團隊 大部分算法（例如HCF, DeepLMCF）只是用在大量數據上訓練好的(pretrain)的一些網絡如VGG作爲特徵提取器，這些做法證實利用CNN深度特徵對跟蹤結果有顯著提升。 但是畢竟clssification 和 tracking是兩個不同的課題 （predicting object class labels VS locating t
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相關文章
- 1. MDNet: Learning Multi-Domain Convolutional Neural Networks for Visual Tracking
- 2. Learning Multi-Domain Convolutional Neural Networks for Visual Tracking
- 3. Learning Multi-Domain Convolutional Neural Networks for Visual Tracking CVPR 2016 閱讀筆記
- 4. Learning Multi-Domain Convolutional Neural Networks for Visual Tracking 論文筆記
- 5. 深度學習筆記（一）：Learning Multi-Domain Convolutional Neural Networks for Visual Tracking
- 6. 論文閱讀：《Convolutional Neural Networks for Sentence Classification》
- 7. 論文閱讀-Fast Algorithms for Convolutional Neural Networks
- 8. ROLO:Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object Tracking
- 9. 論文閱讀：Learning Dual Convolutional Neural Networks for Low-Level Vision
- 10. 論文閱讀筆記（一）：Learning Dual Convolutional Neural Networks for Low-Level Vision