SGM-Nets: Semi-global matching with neural networks
這是kitti上排名靠前的文章 且最近希望能夠從傳統方法的角度上看看可否突破 因此這篇文章必定細讀之 摘： SGM是一個常用的規範化方法，以其較高的精度以及較快的速率聞名於世。 通過改變SGM的懲罰參數來調節視差預測圖是否平滑還是不連續，SGM能夠取得一個較好的結果。所以要用好非常的不容易而且跟使用者的經驗有很大的關係。 因此本文提出一種這個參數估計的方法，美其名曰 SGM-Net ，由卷積神經網
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