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《Learning Enriched Features for Real Image Restoration and Enhancement》
時間 2020-12-26
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一、論文 《Learning Enriched Features for Real Image Restoration and Enhancement》 摘要:以從降級版本中恢復高質量圖像內容爲目標,圖像恢復在監視,計算攝影,醫學成像和遙感等領域擁有衆多應用。 最近,卷積神經網絡(CNN)與傳統的圖像恢復任務方法相比取得了巨大的進步。 現有的基於CNN的方法通常以全分辨率或漸進式低分辨率表示形式運
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相關文章
1.
Optimized contrast enhancement for real-time image and video dehazing
2.
Discriminative Transfer Learning for General Image Restoration
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