[論文閱讀] CTPN---Detecting Text in Natural Image with Connectionist Text Proposal Network
這篇論文思路和Faster RCNN是差不多的。總體來說，就是先通過RPN(Region Proposal Network)來提取proposal，然後再對提取得到的proposal進行classification。 文章對Faster RCNN有以下幾點改進： Faster RCNN中使用的3種size和3種長寬比組合的9種anchor，但是CTPN中，他固定了anchor爲16px(vgg16
相關文章
- 1. Detecting Text in Natural Image with Connectionist Text Proposal Network論文筆記
- 2. 論文閱讀學習 - CTPN-Detecting Text in Natural Image with Connectionist Text Proposal Network
- 3. 翻譯CTPN：Detecting Text in Natural Image with Connectionist Text Proposal Network
- 4. 【Paper Reading】【CTPN: Detecting Text in Natural Image with Connectionist Text Proposal Network】
- 5. 【ECCV2016】Detecting Text in Natural Image with Connectionist Text Proposal Network
- 6. CTPN（Detecting Text in Natural Image with Connectionist Text Proposal Network）算法詳解
- 7. Connectionist Text Proposal Network
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相關文章
- 1. Detecting Text in Natural Image with Connectionist Text Proposal Network論文筆記
- 2. 論文閱讀學習 - CTPN-Detecting Text in Natural Image with Connectionist Text Proposal Network
- 3. 翻譯CTPN：Detecting Text in Natural Image with Connectionist Text Proposal Network
- 4. 【Paper Reading】【CTPN: Detecting Text in Natural Image with Connectionist Text Proposal Network】
- 5. 【ECCV2016】Detecting Text in Natural Image with Connectionist Text Proposal Network
- 6. CTPN（Detecting Text in Natural Image with Connectionist Text Proposal Network）算法詳解
- 7. Connectionist Text Proposal Network
- 8. 論文閱讀CENet-Detecting Text in the Wild with Deep character Embedding Network
- 9. 【論文閱讀】Arbitrary Shape Scene Text Detection with Adaptive Text Region Representation
- 10. 論文閱讀：Text-to-Text Pre-Training for Data-to-Text Tasks