【姿態估計文章閱讀】Efficient Object Localization Using Convolutional Networks【大佬文，每一個實驗都值得一看】
一、這是大佬們的一篇文章，算是比較早的利用CNN預測heatmap來做姿態估計的文章，上傳時間2015年。 二、這篇文章的核心思想： 1、pooling層能爲網絡增強一些「局部不變性」、「旋轉不變性」之類的能力，也能降低參數等種種優點的同時對於迴歸heatmap的任務卻會帶來location的精度損失。因此提出了一種新的結構，用於彌補pooling的負效應，「position ref
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相關文章
- 1. OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks論文閱讀筆記
- 2. 對 OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks 一文的理解...
- 3. 【文章閱讀】Submanifold Sparse Convolutional Networks
- 4. 【OverFeat】《OverFeat：Integrated Recognition, Localization and Detection using Convolutional Networks》
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- 8. OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
- 9. 論文閱讀：EfficientDet: Scalable and Efficient Object Detection
- 10. 【姿態估計文章閱讀】Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation