Deep Neural Network for Fast and Accurate Single Image Super-Resolution via Channel-Attention-based
本文提出現行超分網絡中存在大量參數，運算複雜，爲了解決這些問題，本文提出了將一維卷積與二維卷積聯合起來使用以定向提取特徵，並減少參數。 該網絡的總體架構較爲簡單，將低分辨率圖片輸入後經過33的卷積提取淺層特徵後，輸入到OAM塊中進一步提取定向特徵，通過全局注意力機制，最後通過兩個33卷積降維hou，亞像素到高分辨率圖片。 此網絡的創新點主要在於oam中的利用1維卷積進行定向採樣，從而更充分的提取水
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