ROLO:Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object Tracking
來源：ArXiv：1607.05781v1 Jul 2016 Abstract： 本文研發了一種可以進行空間監督的循環卷積網絡用以object tracking。該網絡利用位置的歷史信息和由神經網絡學習到的特徵。受bbox的影響，研究LSTM在temporal domain的迴歸能力，並且建議連接由卷積網絡產生的高層次的視覺特徵with region information。本文特色是迴歸，使用回
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相關文章
- 1. Learning Multi-Domain Convolutional Neural Networks for Visual Tracking
- 2. MDNet: Learning Multi-Domain Convolutional Neural Networks for Visual Tracking
- 3. SiamFC:Fully-Convolutional Siamese Networks for Object Tracking
- 4. Recurrent Convolutional Neural Networks for Text Classification
- 5. Fully-Convolutional Siamese Networks for Object Tracking
- 6. CS231n Convolutional Neural Networks for Visual Recognition
- 7. visual tracking 經典文獻翻譯（1）- Fully-Convolutional Siamese Networks for Object Tracking
- 8. Convolutional Neural Networks for Visual Recognition
- 9. PaperReading:Multi-Object Tracking with Quadruplet Convolutional Neural Networks
- 10. 《Constrained Convolutional Neural Networks for Weakly Supervised Segmentation》翻譯