《Bottom-up Object Detection by Grouping Extreme and Center Points》論文解讀
《Bottom-up Object Detection by Grouping Extreme and Center Points》論文解讀 這是CVPR2019關於目標檢測的一篇論文，隨着深度學習的出現，目標檢測從由點及面逐漸發展到基於區域的識別問題。最先進的算法枚舉一個幾乎詳盡的對象位置列表，並將每個位置分類爲：對象與否。在本文中，作者想證明由點及面的方法仍然具有競爭力。 Introducti
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相關文章
- 1. ExtremeNet:Bottom-up Object Detection by Grouping Extreme and Center Points
- 2. 論文閱讀：Bottom-up Object Detection by Grouping Extreme and Center Points
- 3. 【論文筆記】：Bottom-up Object Detection by Grouping Extreme and Center Points
- 4. Bottom-up Object Detection by Grouping Extreme and Center Points 論文筆記
- 5. 論文筆記：Bottom-up Object Detection by Grouping Extreme and Center Points (CVPR 2019)
- 6. Bottom-up Object Detection by Grouping Extreme and Center Points 解讀
- 7. 筆記九：論文閱讀Bottom-up Object Detection by Grouping Extreme and Center Points
- 8. 目標檢測論文閱讀筆記：《Bottom-up Object Detection by Grouping Extreme and Center Points》
- 9. Anchor-free系列——Bottom-up Object Detection by Grouping Extreme and Center Points
- 10. 【ExtremeNet】: Bottom-up Object Detection by Grouping Extreme and Center Points